Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device

ABSTRACT

A three-dimensional data encoding method of encoding three-dimensional points each having an attribute information item includes: classifying each of the three-dimensional points into any of layers including a first layer and a second layer; and arithmetic-encoding an attribute information item of a current three-dimensional point among the three-dimensional points with reference to a first encoding table when the current three-dimensional point is at the first layer, and with reference to a second encoding table not dependent on the first encoding table when the current three-dimensional point is at the second layer.

BACKGROUND 1. Technical Field

The present disclosure relates to a three-dimensional data encodingmethod, a three-dimensional data decoding method, a three-dimensionaldata encoding device, and a three-dimensional data decoding device.

2. Description of the Related Art

Devices or services utilizing three-dimensional data are expected tofind their widespread use in a wide range of fields, such as computervision that enables autonomous operations of cars or robots, mapinformation, monitoring, infrastructure inspection, and videodistribution. Three-dimensional data is obtained through various meansincluding a distance sensor such as a rangefinder, as well as a stereocamera and a combination of a plurality of monocular cameras.

Methods of representing three-dimensional data include a method known asa point cloud scheme that represents the shape of a three-dimensionalstructure by a point group (point cloud) in a three-dimensional space.In the point cloud scheme, the positions and colors of a point cloud arestored. While point cloud is expected to be a mainstream method ofrepresenting three-dimensional data, a massive amount of data of a pointcloud necessitates compression of the amount of three-dimensional databy encoding for accumulation and transmission, as in the case of atwo-dimensional moving picture (examples include MPEG-4 AVC and HEVCstandardized by MPEG).

Meanwhile, point cloud compression is partially supported by, forexample, an open-source library (Point Cloud Library) for pointcloud-related processing.

Furthermore, a technique for searching for and displaying a facilitylocated in the surroundings of the vehicle is known (for example, seeInternational Publication WO 2014/020663).

SUMMARY

There has been a demand for reducing the code amount in encoding ofthree-dimensional data.

The present disclosure has an object to provide a three-dimensional dataencoding method, a three-dimensional data decoding method, athree-dimensional data encoding device, or a three-dimensional datadecoding device that is capable of reducing the code amount.

In accordance with an aspect of the present disclosure, athree-dimensional data encoding method of encoding a plurality ofthree-dimensional points each having an attribute information itemincludes: classifying each of the plurality of three-dimensional pointsinto any of a plurality of layers including a first layer and a secondlayer; and arithmetic-encoding an attribute information item of acurrent three-dimensional point among the plurality of three-dimensionalpoints, the arithmetic encoding being performed with reference to afirst encoding table when the current three-dimensional point is at thefirst layer, and with reference to a second encoding table not dependenton the first encoding table when the current three-dimensional point isat the second layer.

In accordance with another aspect of the present disclosure, athree-dimensional data decoding method of decoding a plurality ofencoded three-dimensional points each having an attribute informationitem includes: classifying each of the plurality of encodedthree-dimensional points into any of a plurality of layers including afirst layer and a second layer; and arithmetic-decoding an attributeinformation item of a current three-dimensional point among theplurality of encoded three-dimensional points included in a bit stream,the arithmetic decoding being performed with reference to a firstdecoding table when the current three-dimensional point is at the firstlayer and with reference to a second decoding table not dependent on thefirst decoding table when the current three-dimensional point is at thesecond layer.

The present disclosure can provide a three-dimensional data encodingmethod, a three-dimensional data decoding method, a three-dimensionaldata encoding device, or a three-dimensional data decoding device thatis capable of reducing code amount.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a diagram showing the structure of encoded three-dimensionaldata according to Embodiment 1.

FIG. 2 is a diagram showing an example of prediction structures amongSPCs that belong to the lowermost layer in a GOS according to Embodiment1.

FIG. 3 is a diagram showing an example of prediction structures amonglayers according to Embodiment 1.

FIG. 4 is a diagram showing an example order of encoding GOSs accordingto Embodiment 1.

FIG. 5 is a diagram showing an example order of encoding GOSs accordingto Embodiment 1.

FIG. 6 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 1.

FIG. 7 is a flowchart of encoding processes according to Embodiment 1.

FIG. 8 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 1.

FIG. 9 is a flowchart of decoding processes according to Embodiment 1.

FIG. 10 is a diagram showing an example of meta information according toEmbodiment 1.

FIG. 11 is a diagram showing an example structure of a SWLD according toEmbodiment 2.

FIG. 12 is a diagram showing example operations performed by a serverand a client according to Embodiment 2.

FIG. 13 is a diagram showing example operations performed by the serverand a client according to Embodiment 2.

FIG. 14 is a diagram showing example operations performed by the serverand the clients according to Embodiment 2.

FIG. 15 is a diagram showing example operations performed by the serverand the clients according to Embodiment 2.

FIG. 16 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 2.

FIG. 17 is a flowchart of encoding processes according to Embodiment 2.

FIG. 18 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 2.

FIG. 19 is a flowchart of decoding processes according to Embodiment 2.

FIG. 20 is a diagram showing an example structure of a WLD according toEmbodiment 2.

FIG. 21 is a diagram showing an example octree structure of the WLDaccording to Embodiment 2.

FIG. 22 is a diagram showing an example structure of a SWLD according toEmbodiment 2.

FIG. 23 is a diagram showing an example octree structure of the SWLDaccording to Embodiment 2.

FIG. 24 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 3.

FIG. 25 is a block diagram of a three-dimensional data transmissiondevice according to Embodiment 3.

FIG. 26 is a block diagram of a three-dimensional information processingdevice according to Embodiment 4.

FIG. 27 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 5.

FIG. 28 is a diagram showing a structure of a system according toEmbodiment 6.

FIG. 29 is a block diagram of a client device according to Embodiment 6.

FIG. 30 is a block diagram of a server according to Embodiment 6.

FIG. 31 is a flowchart of a three-dimensional data creation processperformed by the client device according to Embodiment 6.

FIG. 32 is a flowchart of a sensor information transmission processperformed by the client device according to Embodiment 6.

FIG. 33 is a flowchart of a three-dimensional data creation processperformed by the server according to Embodiment 6.

FIG. 34 is a flowchart of a three-dimensional map transmission processperformed by the server according to Embodiment 6.

FIG. 35 is a diagram showing a structure of a variation of the systemaccording to Embodiment 6.

FIG. 36 is a diagram showing a structure of the server and clientdevices according to Embodiment 6.

FIG. 37 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 7.

FIG. 38 is a diagram showing an example of a prediction residualaccording to Embodiment 7.

FIG. 39 is a diagram showing an example of a volume according toEmbodiment 7.

FIG. 40 is a diagram showing an example of an octree representation ofthe volume according to Embodiment 7.

FIG. 41 is a diagram showing an example of bit sequences of the volumeaccording to Embodiment 7.

FIG. 42 is a diagram showing an example of an octree representation of avolume according to Embodiment 7.

FIG. 43 is a diagram showing an example of the volume according toEmbodiment 7.

FIG. 44 is a diagram for describing an intra prediction processaccording to Embodiment 7.

FIG. 45 is a diagram for describing a rotation and translation processaccording to Embodiment 7.

FIG. 46 is a diagram showing an example syntax of an RT flag and RTinformation according to Embodiment 7.

FIG. 47 is a diagram for describing an inter prediction processaccording to Embodiment 7.

FIG. 48 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 7.

FIG. 49 is a flowchart of a three-dimensional data encoding processperformed by the three-dimensional data encoding device according toEmbodiment 7.

FIG. 50 is a flowchart of a three-dimensional data decoding processperformed by the three-dimensional data decoding device according toEmbodiment 7.

FIG. 51 is a diagram illustrating a reference relationship in an octreestructure according to Embodiment 8.

FIG. 52 is a diagram illustrating a reference relationship in a spatialregion according to Embodiment 8.

FIG. 53 is a diagram illustrating an example of neighbor reference nodesaccording to Embodiment 8.

FIG. 54 is a diagram illustrating a relationship between a parent nodeand nodes according to Embodiment 8.

FIG. 55 is a diagram illustrating an example of an occupancy code of theparent node according to Embodiment 8.

FIG. 56 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 8.

FIG. 57 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 8.

FIG. 58 is a flowchart of a three-dimensional data encoding processaccording to Embodiment 8.

FIG. 59 is a flowchart of a three-dimensional data decoding processaccording to Embodiment 8.

FIG. 60 is a diagram illustrating an example of selecting a coding tableaccording to Embodiment 8.

FIG. 61 is a diagram illustrating a reference relationship in a spatialregion according to Variation 1 of Embodiment 8.

FIG. 62 is a diagram illustrating an example of a syntax of headerinformation according to Variation 1 of Embodiment 8.

FIG. 63 is a diagram illustrating an example of a syntax of headerinformation according to Variation 1 of Embodiment 8.

FIG. 64 is a diagram illustrating an example of neighbor reference nodesaccording to Variation 2 of Embodiment 8.

FIG. 65 is a diagram illustrating an example of a current node andneighbor nodes according to Variation 2 of Embodiment 8.

FIG. 66 is a diagram illustrating a reference relationship in an octreestructure according to Variation 3 of Embodiment 8.

FIG. 67 is a diagram illustrating a reference relationship in a spatialregion according to Variation 3 of Embodiment 8.

FIG. 68 is a diagram illustrating an example of three-dimensional pointsaccording to Embodiment 9.

FIG. 69 is a diagram illustrating an example of setting LoDs accordingto Embodiment 9.

FIG. 70 is a diagram illustrating an example of setting LoDs accordingto Embodiment 9.

FIG. 71 is a diagram illustrating an example of attribute information tobe used for predicted values according to Embodiment 9.

FIG. 72 is a diagram illustrating examples of exponential-Golomb codesaccording to Embodiment 9.

FIG. 73 is a diagram indicating a process on exponential-Golomb codesaccording to Embodiment 9.

FIG. 74 is a diagram indicating an example of a syntax in attributeheader according to Embodiment 9.

FIG. 75 is a diagram indicating an example of a syntax in attribute dataaccording to Embodiment 9.

FIG. 76 is a flowchart of a three-dimensional data encoding processaccording to Embodiment 9.

FIG. 77 is a flowchart of an attribute information encoding processaccording to Embodiment 9.

FIG. 78 is a diagram indicating processing on exponential-Golomb codesaccording to Embodiment 9.

FIG. 79 is a diagram indicating an example of a reverse lookup tableindicating relationships between remaining codes and the values thereofaccording to Embodiment 9.

FIG. 80 is a flowchart of a three-dimensional data decoding processaccording to Embodiment 9.

FIG. 81 is a flowchart of an attribute information decoding processaccording to Embodiment 9.

FIG. 82 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 9.

FIG. 83 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 9.

FIG. 84 is a flowchart of a three-dimensional data encoding processaccording to Embodiment 9.

FIG. 85 is a flowchart of a three-dimensional data decoding processaccording to Embodiment 9.

FIG. 86 is a diagram for describing a process in a case where aremaining code according to Embodiment 10 is an exponential Golomb code.

FIG. 87 is a diagram for describing a first example of a process inwhich the three-dimensional data encoding device according to Embodiment10 performs the arithmetic encoding by changing the encoding table foreach level of detail (LoD).

FIG. 88 is a diagram for describing a second example of the process inwhich the three-dimensional data encoding device according to Embodiment10 performs the arithmetic encoding by changing the encoding table foreach LoD.

FIG. 89 is a diagram for describing a third example of the process inwhich the three-dimensional data encoding device according to Embodiment10 performs the arithmetic encoding by changing the encoding table foreach LoD.

FIG. 90 is a diagram for describing a fourth example of the process inwhich the three-dimensional data encoding device according to Embodiment10 performs the arithmetic encoding by changing the encoding table foreach LoD.

FIG. 91 is a diagram for describing a fifth example of the process inwhich the three-dimensional data encoding device according to Embodiment10 performs the arithmetic encoding by changing the encoding table foreach LoD.

FIG. 92 is a diagram for describing a sixth example of the process inwhich the three-dimensional data encoding device according to Embodiment10 performs the arithmetic encoding by changing the encoding table foreach LoD.

FIG. 93 is a flowchart for describing a process of arithmetic encodingof a prediction residual performed by the three-dimensional dataencoding device according to Embodiment 10.

FIG. 94 is a flowchart showing an example of a process in which thethree-dimensional data encoding device according to Embodiment 10arithmetically encodes an n-bit code.

FIG. 95 is a flowchart showing an example of the process in which thethree-dimensional data encoding device according to Embodiment 10arithmetically encodes the remaining code.

FIG. 96 is a flowchart for describing a process of arithmetic decodingof the prediction residual performed by the three-dimensional datadecoding device according to Embodiment 10.

FIG. 97 is a flowchart showing an example of a process in which thethree-dimensional data decoding device according to Embodiment 10arithmetically decodes the arithmetically-encoded data of the n-bitcode.

FIG. 98 is a flowchart showing an example of the process in which thethree-dimensional data decoding device according to Embodiment 10arithmetically decodes the remaining code.

FIG. 99 is a block diagram showing a configuration of an attributeinformation encoder provided in the three-dimensional data encodingdevice according to Embodiment 10.

FIG. 100 is a block diagram showing a configuration of an attributeinformation decoder provided in the three-dimensional data decodingdevice according to Embodiment 10.

FIG. 101 is a diagram showing an example of a case where thethree-dimensional data encoding device according to a variation ofEmbodiment 10 uses an entropy encoding table using an octreerepresentation for arithmetic encoding.

FIG. 102 is a flowchart of a three-dimensional data encoding processincluding an adaptive entropy encoding process using structureinformation according to the variation of Embodiment 10.

FIG. 103 is a flowchart of a three-dimensional data decoding processincluding an adaptive entropy decoding process using the structureinformation according to the variation of Embodiment 10.

FIG. 104 is a flowchart of an initialization process for an encodingtable using structure information according to the variation ofEmbodiment 10.

FIG. 105 is a block diagram of a three-dimensional data encoding deviceaccording to the variation of Embodiment 10.

FIG. 106 is a block diagram of a three-dimensional data decoding deviceaccording to the variation of Embodiment 10.

FIG. 107 is a diagram for describing a process in a case where theremaining code according to the variation of Embodiment 10 is anexponential Golomb code.

FIG. 108 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the variation ofEmbodiment 10 performs the arithmetic encoding by initializing theencoding table each time a switching among LoDs occurs.

FIG. 109 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the variation ofEmbodiment 10 performs the arithmetic encoding by initializing theencoding table based on EndLoDCT.

FIG. 110 is a diagram for describing an example of the process in whichthe three-dimensional data encoding device according to the variation ofEmbodiment 10 performs the arithmetic encoding by initializing theencoding table based on StartLoDCT.

FIG. 111 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the variation ofEmbodiment 10 performs the arithmetic encoding by initializing theencoding table based on InitLoDCT.

FIG. 112 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the variation ofEmbodiment 10 performs the arithmetic encoding by initializing theencoding table based on InitLoDCT[N].

FIG. 113 is a diagram for describing another example of the process inwhich the three-dimensional data encoding device according to thevariation of Embodiment 10 performs the arithmetic encoding byinitializing the encoding table based on InitLoDCT[N].

FIG. 114 is a diagram showing an example syntax of a bitstream accordingto the variation of Embodiment 10.

FIG. 115 is a flowchart of a three-dimensional data encoding process bythe three-dimensional data encoding device according to the variation ofEmbodiment 10.

FIG. 116 is a flowchart of the attribute information encoding processshown in FIG. 115.

FIG. 117 is a flowchart of a three-dimensional data decoding process bythe three-dimensional data decoding device.

FIG. 118 is a flowchart of the attribute information decoding processshown in FIG. 117.

FIG. 119 is a flowchart of an initialization process for an encodingtable performed by the three-dimensional data encoding device accordingto the variation of Embodiment 10.

FIG. 120 is a block diagram showing a configuration of the attributeinformation encoder provided in the three-dimensional data encodingdevice according to the variation of Embodiment 10.

FIG. 121 is a block diagram showing a configuration of the attributeinformation decoder provided in the three-dimensional data decodingdevice according to the variation of Embodiment 10.

FIG. 122 is a flowchart showing an encoding process by thethree-dimensional data encoding device according to Embodiment 10 andvariations of Embodiment 10.

FIG. 123 is a flowchart showing a decoding process by thethree-dimensional data decoding device according to Embodiment 10 andvariations of Embodiment 10.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In accordance with an aspect of the present disclosure, athree-dimensional data encoding method of encoding a plurality ofthree-dimensional points each having an attribute information itemincludes: classifying each of the plurality of three-dimensional pointsinto any of a plurality of layers including a first layer and a secondlayer; and arithmetic-encoding an attribute information item of acurrent three-dimensional point among the plurality of three-dimensionalpoints, the arithmetic encoding being performed with reference to afirst encoding table when the current three-dimensional point is at thefirst layer, and with reference to a second encoding table not dependenton the first encoding table when the current three-dimensional point isat the second layer.

According to the three-dimensional data encoding method, an attributeinformation item can be encoded using an encoding table appropriate foreach layer, and therefore the code amount of the encoded data of theattribute information item can be reduced.

For example, the first encoding table and the second encoding table aredifferent from each other.

In this case, the three-dimensional data encoding method canarithmetically encode an attribute information item on athree-dimensional point using an encoding table appropriate for eachlayer. Therefore, the three-dimensional data encoding device can furtherimprove the coding efficiency.

For example, each of the plurality of three-dimensional points includesgeometry information indicating a position of the three-dimensionalpoint, and the classifying is performed based on the geometryinformation to cause a higher layer among the plurality of layers tohave a longer distance between three-dimensional points belonging to thehigher layer.

In this case, the three-dimensional data encoding method can encode anattribute information item on a three-dimensional point using anencoding table appropriate for a distance between three-dimensionalpoints in each layer. Therefore, the three-dimensional data encodingdevice can further improve the coding efficiency.

For example, the first layer is higher than the second layer among theplurality of layers, the arithmetic-encoding is performed with referenceto a first encoding table when the current three-dimensional point is ata layer higher than a first threshold layer among the plurality oflayers, and with reference to the second encoding table when the currentthree-dimensional point is at a layer equal to or lower than the firstthreshold layer.

In this case, the three-dimensional data encoding method does not needto use many encoding tables, and can further improve the codingefficiency.

For example, the first layer is higher than the second layer among theplurality of layers, and the arithmetic-encoding includes:arithmetic-encoding attribute information items of all ofthree-dimensional points at the first layer; initializing the firstencoding table after the arithmetic-encoding of the attributeinformation items; and arithmetic-encoding attribute information itemsof three-dimensional points at a layer next to the first layer withreference to the first encoding table initialized in the initializing.

The encoding tables used for the arithmetic encoding for differentlayers in the three-dimensional data encoding method may be encodingtables that are different from each other or encoding tables that aremade independent of each other by initialization thereof. In this case,the three-dimensional data encoding method can improve the codingefficiency with a small number of encoding tables.

For example, the arithmetic-encoding is performed sequentially from ahigher layer among the plurality of layers, when the currentthree-dimensional point is at a layer higher than a second thresholdlayer, initializing the first encoding table, and arithmetic-encodingthe attribute information item of the current three-dimensional pointwith reference to the first encoding table initialized in theinitializing; and when the current three-dimensional point is at a layerequal to or lower than the second threshold layer, arithmetic-encodingthe attribute information item of the current three-dimensional pointwith reference to the second encoding table.

For example, in an upper layer, the three-dimensional points belongingto the layer are at longer distances from each other, so that theprediction is difficult, and as a result, the prediction residualcalculated from the attribute information item can be greater. On theother hand, in a lower layer, the three-dimensional points belonging tothe layer are at shorter distances from each other, so that theprecision of the prediction is high, and as a result, the predictionresidual can be smaller. In short, the probability of the occurrencepattern of the prediction residual can be significantly differentbetween an upper layer and a lower layer. For this reason, thethree-dimensional data encoding method can improve the coding efficiencyby initializing the encoding table used for arithmetically encoding theattribute information item when a plurality of layers are upper layers.

For example, the second encoding table is generated by initializing thefirst encoding table.

In this case, the three-dimensional data encoding method can furtherimprove the coding efficiency.

In accordance with another aspect of the present disclosure, athree-dimensional data decoding method of decoding a plurality ofencoded three-dimensional points each having an attribute informationitem includes: classifying each of the plurality of encodedthree-dimensional points into any of a plurality of layers including afirst layer and a second layer; and arithmetic-decoding an attributeinformation item of a current three-dimensional point among theplurality of encoded three-dimensional points included in a bit stream,the arithmetic decoding being performed with reference to a firstdecoding table when the current three-dimensional point is at the firstlayer and with reference to a second decoding table not dependent on thefirst decoding table when the current three-dimensional point is at thesecond layer.

In this case, the three-dimensional data decoding method canappropriately decode a bitstream of an attribute information itemencoded using an independent encoding table for each layer.

For example, the first decoding table and the second decoding table aredifferent from each other.

In this case, the three-dimensional data decoding method canappropriately decode encoded data produced by arithmetically encoding anattribute information item on a three-dimensional point using anappropriate encoding table for each layer.

For example, each of the plurality of encoded three-dimensional pointsincludes geometry information indicating a position of thethree-dimensional point, and the classifying is performed based on thegeometry information to cause a higher layer among the plurality oflayers to have a longer distance between three-dimensional pointsbelonging to the higher layer.

In this case, the three-dimensional data decoding method canappropriately decode an attribute information item on athree-dimensional point encoded using an encoding table appropriate fordistances between three-dimensional points in each layer.

For example, the first layer is higher than the second layer among theplurality of layers, the arithmetic-decoding is performed with referenceto a first decoding table when the current three-dimensional point is ata layer higher than a first threshold layer among the plurality oflayers, and with reference to the second decoding table when the currentthree-dimensional point is at a layer equal to or lower than the firstthreshold layer.

In this case, the three-dimensional data decoding method canappropriately decode an attribute information item on athree-dimensional point encoded based on the first threshold layer.

For example, the first layer is higher than the second layer among theplurality of layers, and the arithmetic-decoding includes:arithmetic-decoding attribute information items of all ofthree-dimensional points at the first layer; initializing the firstdecoding table after the arithmetic-decoding of the attributeinformation items; and arithmetic-decoding attribute information itemsof three-dimensional points at a layer next to the first layer withreference to the first decoding table initialized in the initializing.

In this case, the three-dimensional data decoding method canappropriately decode an attribute information item on athree-dimensional point encoded using an initialized encoding table.

For example, the arithmetic-decoding is performed sequentially from ahigher layer among the plurality of layers, when the currentthree-dimensional point is at a layer higher than a second thresholdlayer, initializing the first decoding table, and arithmetic-decodingthe attribute information item of the current three-dimensional pointwith reference to the first decoding table initialized in theinitializing; and when the current three-dimensional point is at a layerequal to or lower than the second threshold layer, arithmetic-decodingthe attribute information item of the current three-dimensional pointwith reference to the second decoding table.

In this case, the three-dimensional data decoding method canappropriately decode each of attribute information items on a pluralityof three-dimensional points encoded using an encoding table initializedfor some layer.

For example, the second decoding table is generated by initializing thefirst decoding table.

The decoding tables used for the arithmetic decoding for differentlayers in the three-dimensional data decoding method may be decodingtables that are different from each other or decoding tables that aremade independent of each other by initialization thereof. In this way,even if attribute information items on three-dimensional points in eachlayer are encoded using an initialized encoding table, thethree-dimensional data decoding method can appropriately decode encodedattribute information items on the three-dimensional points.

In accordance with still another aspect of the present disclosure, athree-dimensional data encoding device encodes a plurality ofthree-dimensional points each having an attribute information item, thedevice including: a processor; and a memory, wherein by using thememory, the processor performs: classifying each of the plurality ofthree-dimensional points into any of a plurality of layers including afirst layer and a second layer; and arithmetic-encoding an attributeinformation item of a current three-dimensional point among theplurality of three-dimensional points, the arithmetic encoding beingperformed with reference to a first encoding table when the currentthree-dimensional point is at the first layer, and with reference to asecond encoding table not dependent on the first encoding table when thecurrent three-dimensional point is at the second layer.

The three-dimensional data encoding device can encode an attributeinformation item using an encoding table appropriate for each layer, andtherefore can reduce the code amount of encoded data of the attributeinformation item.

In accordance with still another aspect of the present disclosure, athree-dimensional data decoding device decodes a plurality of encodedthree-dimensional points each having an attribute information item, thedevice including: a processor; and a memory, wherein by using thememory, the processor performs: classifying each of the plurality ofencoded three-dimensional points into any of a plurality of layersincluding a first layer and a second layer; and arithmetic-decoding anattribute information item of a current three-dimensional point amongthe plurality of encoded three-dimensional points included in a bitstream, the arithmetic decoding being performed with reference to afirst decoding table when the current three-dimensional point is at thefirst layer and with reference to a second decoding table not dependenton the first decoding table when the current three-dimensional point isat the second layer.

The three-dimensional data decoding device can appropriately decode abitstream of an attribute information item encoded using an independentencoding table for each layer.

It is to be noted that these general or specific aspects may beimplemented as a system, a method, an integrated circuit, a computerprogram, or a computer-readable recording medium such as a CD-ROM, ormay be implemented as any combination of a system, a method, anintegrated circuit, a computer program, and a recording medium.

The following describes embodiments with reference to the drawings. Itis to be noted that the following embodiments indicate exemplaryembodiments of the present disclosure. The numerical values, shapes,materials, constituent elements, the arrangement and connection of theconstituent elements, steps, the processing order of the steps, etc.indicated in the following embodiments are mere examples, and thus arenot intended to limit the present disclosure. Of the constituentelements described in the following embodiments, constituent elementsnot recited in any one of the independent claims that indicate thebroadest concepts will be described as optional constituent elements.

Embodiment 1

First, the data structure of encoded three-dimensional data (hereinafteralso referred to as encoded data) according to the present embodimentwill be described. FIG. 1 is a diagram showing the structure of encodedthree-dimensional data according to the present embodiment.

In the present embodiment, a three-dimensional space is divided intospaces (SPCs), which correspond to pictures in moving picture encoding,and the three-dimensional data is encoded on a SPC-by-SPC basis. EachSPC is further divided into volumes (VLMs), which correspond tomacroblocks, etc. in moving picture encoding, and predictions andtransforms are performed on a VLM-by-VLM basis. Each volume includes aplurality of voxels (VXLs), each being a minimum unit in which positioncoordinates are associated. Note that prediction is a process ofgenerating predictive three-dimensional data analogous to a currentprocessing unit by referring to another processing unit, and encoding adifferential between the predictive three-dimensional data and thecurrent processing unit, as in the case of predictions performed ontwo-dimensional images. Such prediction includes not only spatialprediction in which another prediction unit corresponding to the sametime is referred to, but also temporal prediction in which a predictionunit corresponding to a different time is referred to.

When encoding a three-dimensional space represented by point cloud datasuch as a point cloud, for example, the three-dimensional data encodingdevice (hereinafter also referred to as the encoding device) encodes thepoints in the point cloud or points included in the respective voxels ina collective manner, in accordance with a voxel size. Finer voxelsenable a highly-precise representation of the three-dimensional shape ofa point cloud, while larger voxels enable a rough representation of thethree-dimensional shape of a point cloud.

Note that the following describes the case where three-dimensional datais a point cloud, but three-dimensional data is not limited to a pointcloud, and thus three-dimensional data of any format may be employed.

Also note that voxels with a hierarchical structure may be used. In sucha case, when the hierarchy includes n levels, whether a sampling pointis included in the n-lth level or lower levels (levels below the n-thlevel) may be sequentially indicated. For example, when only the n-thlevel is decoded, and the n-lth level or lower levels include a samplingpoint, the n-th level can be decoded on the assumption that a samplingpoint is included at the center of a voxel in the n-th level.

Also, the encoding device obtains point cloud data, using, for example,a distance sensor, a stereo camera, a monocular camera, a gyroscopesensor, or an inertial sensor.

As in the case of moving picture encoding, each SPC is classified intoone of at least the three prediction structures that include: intra SPC(I-SPC), which is individually decodable; predictive SPC (P-SPC) capableof only a unidirectional reference; and bidirectional SPC (B-SPC)capable of bidirectional references. Each SPC includes two types of timeinformation: decoding time and display time.

Furthermore, as shown in FIG. 1, a processing unit that includes aplurality of SPCs is a group of spaces (GOS), which is a random accessunit. Also, a processing unit that includes a plurality of GOSs is aworld (WLD).

The spatial region occupied by each world is associated with an absoluteposition on earth, by use of, for example, GPS, or latitude andlongitude information. Such position information is stored asmeta-information. Note that meta-information may be included in encodeddata, or may be transmitted separately from the encoded data.

Also, inside a GOS, all SPCs may be three-dimensionally adjacent to oneanother, or there may be a SPC that is not three-dimensionally adjacentto another SPC.

Note that the following also describes processes such as encoding,decoding, and reference to be performed on three-dimensional dataincluded in processing units such as GOS, SPC, and VLM, simply asperforming encoding/to encode, decoding/to decode, referring to, etc. ona processing unit. Also note that three-dimensional data included in aprocessing unit includes, for example, at least one pair of a spatialposition such as three-dimensional coordinates and an attribute valuesuch as color information.

Next, the prediction structures among SPCs in a GOS will be described. Aplurality of SPCs in the same GOS or a plurality of VLMs in the same SPCoccupy mutually different spaces, while having the same time information(the decoding time and the display time).

A SPC in a GOS that comes first in the decoding order is an I-SPC. GOSscome in two types: closed GOS and open GOS. A closed GOS is a GOS inwhich all SPCs in the GOS are decodable when decoding starts from thefirst I-SPC. Meanwhile, an open GOS is a GOS in which a different GOS isreferred to in one or more SPCs preceding the first I-SPC in the GOS inthe display time, and thus cannot be singly decoded.

Note that in the case of encoded data of map information, for example, aWLD is sometimes decoded in the backward direction, which is opposite tothe encoding order, and thus backward reproduction is difficult whenGOSs are interdependent. In such a case, a closed GOS is basically used.

Each GOS has a layer structure in height direction, and SPCs aresequentially encoded or decoded from SPCs in the bottom layer.

FIG. 2 is a diagram showing an example of prediction structures amongSPCs that belong to the lowermost layer in a GOS. FIG. 3 is a diagramshowing an example of prediction structures among layers.

A GOS includes at least one I-SPC. Of the objects in a three-dimensionalspace, such as a person, an animal, a car, a bicycle, a signal, and abuilding serving as a landmark, a small-sized object is especiallyeffective when encoded as an I-SPC. When decoding a GOS at a lowthroughput or at a high speed, for example, the three-dimensional datadecoding device (hereinafter also referred to as the decoding device)decodes only I-SPC(s) in the GOS.

The encoding device may also change the encoding interval or theappearance frequency of I-SPCs, depending on the degree of sparsenessand denseness of the objects in a WLD.

In the structure shown in FIG. 3, the encoding device or the decodingdevice encodes or decodes a plurality of layers sequentially from thebottom layer (layer 1). This increases the priority of data on theground and its vicinity, which involve a larger amount of information,when, for example, a self-driving car is concerned.

Regarding encoded data used for a drone, for example, encoding ordecoding may be performed sequentially from SPCs in the top layer in aGOS in height direction.

The encoding device or the decoding device may also encode or decode aplurality of layers in a manner that the decoding device can have arough grasp of a GOS first, and then the resolution is graduallyincreased. The encoding device or the decoding device may performencoding or decoding in the order of layers 3, 8, 1, 9 . . . , forexample.

Next, the handling of static objects and dynamic objects will bedescribed.

A three-dimensional space includes scenes or still objects such as abuilding and a road (hereinafter collectively referred to as staticobjects), and objects with motion such as a car and a person(hereinafter collectively referred to as dynamic objects). Objectdetection is separately performed by, for example, extracting keypointsfrom point cloud data, or from video of a camera such as a stereocamera. In this description, an example method of encoding a dynamicobject will be described.

A first method is a method in which a static object and a dynamic objectare encoded without distinction. A second method is a method in which adistinction is made between a static object and a dynamic object on thebasis of identification information.

For example, a GOS is used as an identification unit. In such a case, adistinction is made between a GOS that includes SPCs constituting astatic object and a GOS that includes SPCs constituting a dynamicobject, on the basis of identification information stored in the encodeddata or stored separately from the encoded data.

Alternatively, a SPC may be used as an identification unit. In such acase, a distinction is made between a SPC that includes VLMsconstituting a static object and a SPC that includes VLMs constituting adynamic object, on the basis of the identification information thusdescribed.

Alternatively, a VLM or a VXL may be used as an identification unit. Insuch a case, a distinction is made between a VLM or a VXL that includesa static object and a VLM or a VXL that includes a dynamic object, onthe basis of the identification information thus described.

The encoding device may also encode a dynamic object as at least one VLMor SPC, and may encode a VLM or a SPC including a static object and aSPC including a dynamic object as mutually different GOSs. When the GOSsize is variable depending on the size of a dynamic object, the encodingdevice separately stores the GOS size as meta-information.

The encoding device may also encode a static object and a dynamic objectseparately from each other, and may superimpose the dynamic object ontoa world constituted by static objects. In such a case, the dynamicobject is constituted by at least one SPC, and each SPC is associatedwith at least one SPC constituting the static object onto which the eachSPC is to be superimposed. Note that a dynamic object may be representednot by SPC(s) but by at least one VLM or VXL.

The encoding device may also encode a static object and a dynamic objectas mutually different streams.

The encoding device may also generate a GOS that includes at least oneSPC constituting a dynamic object. The encoding device may further setthe size of a GOS including a dynamic object (GOS_M) and the size of aGOS including a static object corresponding to the spatial region ofGOS_M at the same size (such that the same spatial region is occupied).This enables superimposition to be performed on a GOS-by-GOS basis.

SPC(s) included in another encoded GOS may be referred to in a P-SPC ora B-SPC constituting a dynamic object. In the case where the position ofa dynamic object temporally changes, and the same dynamic object isencoded as an object in a GOS corresponding to a different time,referring to SPC(s) across GOSs is effective in terms of compressionrate.

The first method and the second method may be selected in accordancewith the intended use of encoded data. When encoded three-dimensionaldata is used as a map, for example, a dynamic object is desired to beseparated, and thus the encoding device uses the second method.Meanwhile, the encoding device uses the first method when the separationof a dynamic object is not required such as in the case wherethree-dimensional data of an event such as a concert and a sports eventis encoded.

The decoding time and the display time of a GOS or a SPC are storable inencoded data or as meta-information. All static objects may have thesame time information. In such a case, the decoding device may determinethe actual decoding time and display time. Alternatively, a differentvalue may be assigned to each GOS or SPC as the decoding time, and thesame value may be assigned as the display time. Furthermore, as in thecase of the decoder model in moving picture encoding such asHypothetical Reference Decoder (HRD) compliant with HEVC, a model may beemployed that ensures that a decoder can perform decoding without failby having a buffer of a predetermined size and by reading a bitstream ata predetermined bit rate in accordance with the decoding times.

Next, the topology of GOSs in a world will be described. The coordinatesof the three-dimensional space in a world are represented by the threecoordinate axes (x axis, y axis, and z axis) that are orthogonal to oneanother. A predetermined rule set for the encoding order of GOSs enablesencoding to be performed such that spatially adjacent GOSs arecontiguous in the encoded data. In an example shown in FIG. 4, forexample, GOSs in the x and z planes are successively encoded. After thecompletion of encoding all GOSs in certain x and z planes, the value ofthe y axis is updated. Stated differently, the world expands in the yaxis direction as the encoding progresses. The GOS index numbers are setin accordance with the encoding order.

Here, the three-dimensional spaces in the respective worlds arepreviously associated one-to-one with absolute geographical coordinatessuch as GPS coordinates or latitude/longitude coordinates.Alternatively, each three-dimensional space may be represented as aposition relative to a previously set reference position. The directionsof the x axis, the y axis, and the z axis in the three-dimensional spaceare represented by directional vectors that are determined on the basisof the latitudes and the longitudes, etc. Such directional vectors arestored together with the encoded data as meta-information.

GOSs have a fixed size, and the encoding device stores such size asmeta-information. The GOS size may be changed depending on, for example,whether it is an urban area or not, or whether it is inside or outsideof a room. Stated differently, the GOS size may be changed in accordancewith the amount or the attributes of objects with information values.Alternatively, in the same world, the encoding device may adaptivelychange the GOS size or the interval between I-SPCs in GOSs in accordancewith the object density, etc. For example, the encoding device sets theGOS size to smaller and the interval between I-SPCs in GOSs to shorter,as the object density is higher.

In an example shown in FIG. 5, to enable random access with a finergranularity, a GOS with a high object density is partitioned into theregions of the third to tenth GOSs. Note that the seventh to tenth GOSsare located behind the third to sixth GOSs.

Next, the structure and the operation flow of the three-dimensional dataencoding device according to the present embodiment will be described.FIG. 6 is a block diagram of three-dimensional data encoding device 100according to the present embodiment. FIG. 7 is a flowchart of an exampleoperation performed by three-dimensional data encoding device 100.

Three-dimensional data encoding device 100 shown in FIG. 6 encodesthree-dimensional data 111, thereby generating encoded three-dimensionaldata 112. Such three-dimensional data encoding device 100 includesobtainer 101, encoding region determiner 102, divider 103, and encoder104.

As shown in FIG. 7, first, obtainer 101 obtains three-dimensional data111, which is point cloud data (S101).

Next, encoding region determiner 102 determines a current region forencoding from among spatial regions corresponding to the obtained pointcloud data (S102). For example, in accordance with the position of auser or a vehicle, encoding region determiner 102 determines, as thecurrent region, a spatial region around such position.

Next, divider 103 divides the point cloud data included in the currentregion into processing units. The processing units here means units suchas GOSs and SPCs described above. The current region here correspondsto, for example, a world described above. More specifically, divider 103divides the point cloud data into processing units on the basis of apredetermined GOS size, or the presence/absence/size of a dynamic object(S103). Divider 103 further determines the starting position of the SPCthat comes first in the encoding order in each GOS.

Next, encoder 104 sequentially encodes a plurality of SPCs in each GOS,thereby generating encoded three-dimensional data 112 (S104).

Note that although an example is described here in which the currentregion is divided into GOSs and SPCs, after which each GOS is encoded,the processing steps are not limited to this order. For example, stepsmay be employed in which the structure of a single GOS is determined,which is followed by the encoding of such GOS, and then the structure ofthe subsequent GOS is determined.

As thus described, three-dimensional data encoding device 100 encodesthree-dimensional data 111, thereby generating encoded three-dimensionaldata 112. More specifically, three-dimensional data encoding device 100divides three-dimensional data into first processing units (GOSs), eachbeing a random access unit and being associated with three-dimensionalcoordinates, divides each of the first processing units (GOSs) intosecond processing units (SPCs), and divides each of the secondprocessing units (SPCs) into third processing units (VLMs). Each of thethird processing units (VLMs) includes at least one voxel (VXL), whichis the minimum unit in which position information is associated.

Next, three-dimensional data encoding device 100 encodes each of thefirst processing units (GOSs), thereby generating encodedthree-dimensional data 112. More specifically, three-dimensional dataencoding device 100 encodes each of the second processing units (SPCs)in each of the first processing units (GOSs). Three-dimensional dataencoding device 100 further encodes each of the third processing units(VLMs) in each of the second processing units (SPCs).

When a current first processing unit (GOS) is a closed GOS, for example,three-dimensional data encoding device 100 encodes a current secondprocessing unit (SPC) included in such current first processing unit(GOS) by referring to another second processing unit (SPC) included inthe current first processing unit (GOS). Stated differently,three-dimensional data encoding device 100 refers to no secondprocessing unit (SPC) included in a first processing unit (GOS) that isdifferent from the current first processing unit (GOS).

Meanwhile, when a current first processing unit (GOS) is an open GOS,three-dimensional data encoding device 100 encodes a current secondprocessing unit (SPC) included in such current first processing unit(GOS) by referring to another second processing unit (SPC) included inthe current first processing unit (GOS) or a second processing unit(SPC) included in a first processing unit (GOS) that is different fromthe current first processing unit (GOS).

Also, three-dimensional data encoding device 100 selects, as the type ofa current second processing unit (SPC), one of the following: a firsttype (I-SPC) in which another second processing unit (SPC) is notreferred to; a second type (P-SPC) in which another single secondprocessing unit (SPC) is referred to; and a third type in which othertwo second processing units (SPC) are referred to. Three-dimensionaldata encoding device 100 encodes the current second processing unit(SPC) in accordance with the selected type.

Next, the structure and the operation flow of the three-dimensional datadecoding device according to the present embodiment will be described.FIG. 8 is a block diagram of three-dimensional data decoding device 200according to the present embodiment. FIG. 9 is a flowchart of an exampleoperation performed by three-dimensional data decoding device 200.

Three-dimensional data decoding device 200 shown in FIG. 8 decodesencoded three-dimensional data 211, thereby generating decodedthree-dimensional data 212. Encoded three-dimensional data 211 here is,for example, encoded three-dimensional data 112 generated bythree-dimensional data encoding device 100. Such three-dimensional datadecoding device 200 includes obtainer 201, decoding start GOS determiner202, decoding SPC determiner 203, and decoder 204.

First, obtainer 201 obtains encoded three-dimensional data 211 (S201).Next, decoding start GOS determiner 202 determines a current GOS fordecoding (S202). More specifically, decoding start GOS determiner 202refers to meta-information stored in encoded three-dimensional data 211or stored separately from the encoded three-dimensional data todetermine, as the current GOS, a GOS that includes a SPC correspondingto the spatial position, the object, or the time from which decoding isto start.

Next, decoding SPC determiner 203 determines the type(s) (I, P, and/orB) of SPCs to be decoded in the GOS (S203). For example, decoding SPCdeterminer 203 determines whether to (1) decode only I-SPC(s), (2) todecode I-SPC(s) and P-SPCs, or (3) to decode SPCs of all types. Notethat the present step may not be performed, when the type(s) of SPCs tobe decoded are previously determined such as when all SPCs arepreviously determined to be decoded.

Next, decoder 204 obtains an address location within encodedthree-dimensional data 211 from which a SPC that comes first in the GOSin the decoding order (the same as the encoding order) starts. Decoder204 obtains the encoded data of the first SPC from the address location,and sequentially decodes the SPCs from such first SPC (S204). Note thatthe address location is stored in the meta-information, etc.

Three-dimensional data decoding device 200 decodes decodedthree-dimensional data 212 as thus described. More specifically,three-dimensional data decoding device 200 decodes each encodedthree-dimensional data 211 of the first processing units (GOSs), eachbeing a random access unit and being associated with three-dimensionalcoordinates, thereby generating decoded three-dimensional data 212 ofthe first processing units (GOSs). Even more specifically,three-dimensional data decoding device 200 decodes each of the secondprocessing units (SPCs) in each of the first processing units (GOSs).Three-dimensional data decoding device 200 further decodes each of thethird processing units (VLMs) in each of the second processing units(SPCs).

The following describes meta-information for random access. Suchmeta-information is generated by three-dimensional data encoding device100, and included in encoded three-dimensional data 112 (211).

In the conventional random access for a two-dimensional moving picture,decoding starts from the first frame in a random access unit that isclose to a specified time. Meanwhile, in addition to times, randomaccess to spaces (coordinates, objects, etc.) is assumed to be performedin a world.

To enable random access to at least three elements of coordinates,objects, and times, tables are prepared that associate the respectiveelements with the GOS index numbers. Furthermore, the GOS index numbersare associated with the addresses of the respective first I-SPCs in theGOSs. FIG. 10 is a diagram showing example tables included in themeta-information. Note that not all the tables shown in FIG. 10 arerequired to be used, and thus at least one of the tables is used.

The following describes an example in which random access is performedfrom coordinates as a starting point. To access the coordinates (x2, y2,and z2), the coordinates-GOS table is first referred to, which indicatesthat the point corresponding to the coordinates (x2, y2, and z2) isincluded in the second GOS. Next, the GOS-address table is referred to,which indicates that the address of the first I-SPC in the second GOS isaddr(2). As such, decoder 204 obtains data from this address to startdecoding.

Note that the addresses may either be logical addresses or physicaladdresses of an HDD or a memory. Alternatively, information thatidentifies file segments may be used instead of addresses. File segmentsare, for example, units obtained by segmenting at least one GOS, etc.

When an object spans across a plurality of GOSs, the object-GOS tablemay show a plurality of GOSs to which such object belongs. When suchplurality of GOSs are closed GOSs, the encoding device and the decodingdevice can perform encoding or decoding in parallel. Meanwhile, whensuch plurality of GOSs are open GOSs, a higher compression efficiency isachieved by the plurality of GOSs referring to each other.

Example objects include a person, an animal, a car, a bicycle, a signal,and a building serving as a landmark. For example, three-dimensionaldata encoding device 100 extracts keypoints specific to an object from athree-dimensional point cloud, etc., when encoding a world, and detectsthe object on the basis of such keypoints to set the detected object asa random access point.

As thus described, three-dimensional data encoding device 100 generatesfirst information indicating a plurality of first processing units(GOSs) and the three-dimensional coordinates associated with therespective first processing units (GOSs). Encoded three-dimensional data112 (211) includes such first information. The first information furtherindicates at least one of objects, times, and data storage locationsthat are associated with the respective first processing units (GOSs).

Three-dimensional data decoding device 200 obtains the first informationfrom encoded three-dimensional data 211. Using such first information,three-dimensional data decoding device 200 identifies encodedthree-dimensional data 211 of the first processing unit that correspondsto the specified three-dimensional coordinates, object, or time, anddecodes encoded three-dimensional data 211.

The following describes an example of other meta-information. Inaddition to the meta-information for random access, three-dimensionaldata encoding device 100 may also generate and store meta-information asdescribed below, and three-dimensional data decoding device 200 may usesuch meta-information at the time of decoding.

When three-dimensional data is used as map information, for example, aprofile is defined in accordance with the intended use, and informationindicating such profile may be included in meta-information. Forexample, a profile is defined for an urban or a suburban area, or for aflying object, and the maximum or minimum size, etc. of a world, a SPCor a VLM, etc. is defined in each profile. For example, more detailedinformation is required for an urban area than for a suburban area, andthus the minimum VLM size is set to small.

The meta-information may include tag values indicating object types.Each of such tag values is associated with VLMs, SPCs, or GOSs thatconstitute an object. For example, a tag value may be set for eachobject type in a manner, for example, that the tag value “0” indicates“person,” the tag value “1” indicates “car,” and the tag value “2”indicates “signal”. Alternatively, when an object type is hard to judge,or such judgment is not required, a tag value may be used that indicatesthe size or the attribute indicating, for example, whether an object isa dynamic object or a static object.

The meta-information may also include information indicating a range ofthe spatial region occupied by a world.

The meta-information may also store the SPC or VXL size as headerinformation common to the whole stream of the encoded data or to aplurality of SPCs, such as SPCs in a GOS.

The meta-information may also include identification information on adistance sensor or a camera that has been used to generate a pointcloud, or information indicating the positional accuracy of a pointcloud in the point cloud.

The meta-information may also include information indicating whether aworld is made only of static objects or includes a dynamic object.

The following describes variations of the present embodiment.

The encoding device or the decoding device may encode or decode two ormore mutually different SPCs or GOSs in parallel. GOSs to be encoded ordecoded in parallel can be determined on the basis of meta-information,etc. indicating the spatial positions of the GOSs.

When three-dimensional data is used as a spatial map for use by a car ora flying object, etc. in traveling, or for creation of such a spatialmap, for example, the encoding device or the decoding device may encodeor decode GOSs or SPCs included in a space that is identified on thebasis of GPS information, the route information, the zoom magnification,etc.

The decoding device may also start decoding sequentially from a spacethat is close to the self-location or the traveling route. The encodingdevice or the decoding device may give a lower priority to a spacedistant from the self-location or the traveling route than the priorityof a nearby space to encode or decode such distant place. To “give alower priority” means here, for example, to lower the priority in theprocessing sequence, to decrease the resolution (to apply decimation inthe processing), or to lower the image quality (to increase the encodingefficiency by, for example, setting the quantization step to larger).

When decoding encoded data that is hierarchically encoded in a space,the decoding device may decode only the bottom layer in the hierarchy.

The decoding device may also start decoding preferentially from thebottom layer of the hierarchy in accordance with the zoom magnificationor the intended use of the map.

For self-location estimation or object recognition, etc. involved in theself-driving of a car or a robot, the encoding device or the decodingdevice may encode or decode regions at a lower resolution, except for aregion that is lower than or at a specified height from the ground (theregion to be recognized).

The encoding device may also encode point clouds representing thespatial shapes of a room interior and a room exterior separately. Forexample, the separation of a GOS representing a room interior (interiorGOS) and a GOS representing a room exterior (exterior GOS) enables thedecoding device to select a GOS to be decoded in accordance with aviewpoint location, when using the encoded data.

The encoding device may also encode an interior GOS and an exterior GOShaving close coordinates so that such GOSs come adjacent to each otherin an encoded stream. For example, the encoding device associates theidentifiers of such GOSs with each other, and stores informationindicating the associated identifiers into the meta-information that isstored in the encoded stream or stored separately. This enables thedecoding device to refer to the information in the meta-information toidentify an interior GOS and an exterior GOS having close coordinates.

The encoding device may also change the GOS size or the SPC sizedepending on whether a GOS is an interior GOS or an exterior GOS. Forexample, the encoding device sets the size of an interior GOS to smallerthan the size of an exterior GOS. The encoding device may also changethe accuracy of extracting keypoints from a point cloud, or the accuracyof detecting objects, for example, depending on whether a GOS is aninterior GOS or an exterior GOS.

The encoding device may also add, to encoded data, information by whichthe decoding device displays objects with a distinction between adynamic object and a static object. This enables the decoding device todisplay a dynamic object together with, for example, a red box orletters for explanation. Note that the decoding device may display onlya red box or letters for explanation, instead of a dynamic object. Thedecoding device may also display more particular object types. Forexample, a red box may be used for a car, and a yellow box may be usedfor a person.

The encoding device or the decoding device may also determine whether toencode or decode a dynamic object and a static object as a different SPCor GOS, in accordance with, for example, the appearance frequency ofdynamic objects or a ratio between static objects and dynamic objects.For example, when the appearance frequency or the ratio of dynamicobjects exceeds a threshold, a SPC or a GOS including a mixture of adynamic object and a static object is accepted, while when theappearance frequency or the ratio of dynamic objects is below athreshold, a SPC or GOS including a mixture of a dynamic object and astatic object is unaccepted.

When detecting a dynamic object not from a point cloud but fromtwo-dimensional image information of a camera, the encoding device mayseparately obtain information for identifying a detection result (box orletters) and the object position, and encode these items of informationas part of the encoded three-dimensional data. In such a case, thedecoding device superimposes auxiliary information (box or letters)indicating the dynamic object onto a resultant of decoding a staticobject to display it.

The encoding device may also change the sparseness and denseness of VXLsor VLMs in a SPC in accordance with the degree of complexity of theshape of a static object. For example, the encoding device sets VXLs orVLMs at a higher density as the shape of a static object is morecomplex. The encoding device may further determine a quantization step,etc. for quantizing spatial positions or color information in accordancewith the sparseness and denseness of VXLs or VLMs. For example, theencoding device sets the quantization step to smaller as the density ofVXLs or VLMs is higher.

As described above, the encoding device or the decoding device accordingto the present embodiment encodes or decodes a space on a SPC-by-SPCbasis that includes coordinate information.

Furthermore, the encoding device and the decoding device performencoding or decoding on a volume-by-volume basis in a SPC. Each volumeincludes a voxel, which is the minimum unit in which positioninformation is associated.

Also, using a table that associates the respective elements of spatialinformation including coordinates, objects, and times with GOSs or usinga table that associates these elements with each other, the encodingdevice and the decoding device associate any ones of the elements witheach other to perform encoding or decoding. The decoding device uses thevalues of the selected elements to determine the coordinates, andidentifies a volume, a voxel, or a SPC from such coordinates to decode aSPC including such volume or voxel, or the identified SPC.

Furthermore, the encoding device determines a volume, a voxel, or a SPCthat is selectable in accordance with the elements, through extractionof keypoints and object recognition, and encodes the determined volume,voxel, or SPC, as a volume, a voxel, or a SPC to which random access ispossible.

SPCs are classified into three types: I-SPC that is singly encodable ordecodable; P-SPC that is encoded or decoded by referring to any one ofthe processed SPCs; and B-SPC that is encoded or decoded by referring toany two of the processed SPCs.

At least one volume corresponds to a static object or a dynamic object.A SPC including a static object and a SPC including a dynamic object areencoded or decoded as mutually different GOSs. Stated differently, a SPCincluding a static object and a SPC including a dynamic object areassigned to different GOSs.

Dynamic objects are encoded or decoded on an object-by-object basis, andare associated with at least one SPC including a static object. Stateddifferently, a plurality of dynamic objects are individually encoded,and the obtained encoded data of the dynamic objects is associated witha SPC including a static object.

The encoding device and the decoding device give an increased priorityto I-SPC(s) in a GOS to perform encoding or decoding. For example, theencoding device performs encoding in a manner that prevents thedegradation of I-SPCs (in a manner that enables the originalthree-dimensional data to be reproduced with a higher fidelity afterdecoded). The decoding device decodes, for example, only I-SPCs.

The encoding device may change the frequency of using I-SPCs dependingon the sparseness and denseness or the number (amount) of the objects ina world to perform encoding. Stated differently, the encoding devicechanges the frequency of selecting I-SPCs depending on the number or thesparseness and denseness of the objects included in thethree-dimensional data. For example, the encoding device uses I-SPCs ata higher frequency as the density of the objects in a world is higher.

The encoding device also sets random access points on a GOS-by-GOSbasis, and stores information indicating the spatial regionscorresponding to the GOSs into the header information.

The encoding device uses, for example, a default value as the spatialsize of a GOS. Note that the encoding device may change the GOS sizedepending on the number (amount) or the sparseness and denseness ofobjects or dynamic objects. For example, the encoding device sets thespatial size of a GOS to smaller as the density of objects or dynamicobjects is higher or the number of objects or dynamic objects isgreater.

Also, each SPC or volume includes a keypoint group that is derived byuse of information obtained by a sensor such as a depth sensor, agyroscope sensor, or a camera sensor. The coordinates of the keypointsare set at the central positions of the respective voxels. Furthermore,finer voxels enable highly accurate position information.

The keypoint group is derived by use of a plurality of pictures. Aplurality of pictures include at least two types of time information:the actual time information and the same time information common to aplurality of pictures that are associated with SPCs (for example, theencoding time used for rate control, etc.).

Also, encoding or decoding is performed on a GOS-by-GOS basis thatincludes at least one SPC.

The encoding device and the decoding device predict P-SPCs or B-SPCs ina current GOS by referring to SPCs in a processed GOS.

Alternatively, the encoding device and the decoding device predictP-SPCs or B-SPCs in a current GOS, using the processed SPCs in thecurrent GOS, without referring to a different GOS.

Furthermore, the encoding device and the decoding device transmit orreceive an encoded stream on a world-by-world basis that includes atleast one GOS.

Also, a GOS has a layer structure in one direction at least in a world,and the encoding device and the decoding device start encoding ordecoding from the bottom layer. For example, a random accessible GOSbelongs to the lowermost layer. A GOS that belongs to the same layer ora lower layer is referred to in a GOS that belongs to an upper layer.Stated differently, a GOS is spatially divided in a predetermineddirection in advance to have a plurality of layers, each including atleast one SPC. The encoding device and the decoding device encode ordecode each SPC by referring to a SPC included in the same layer as theeach SPC or a SPC included in a layer lower than that of the each SPC.

Also, the encoding device and the decoding device successively encode ordecode GOSs on a world-by-world basis that includes such GOSs. In sodoing, the encoding device and the decoding device write or read outinformation indicating the order (direction) of encoding or decoding asmetadata. Stated differently, the encoded data includes informationindicating the order of encoding a plurality of GOSs.

The encoding device and the decoding device also encode or decodemutually different two or more SPCs or GOSs in parallel.

Furthermore, the encoding device and the decoding device encode ordecode the spatial information (coordinates, size, etc.) on a SPC or aGOS.

The encoding device and the decoding device encode or decode SPCs orGOSs included in an identified space that is identified on the basis ofexternal information on the self-location or/and region size, such asGPS information, route information, or magnification.

The encoding device or the decoding device gives a lower priority to aspace distant from the self-location than the priority of a nearby spaceto perform encoding or decoding.

The encoding device sets a direction at one of the directions in aworld, in accordance with the magnification or the intended use, toencode a GOS having a layer structure in such direction. Also, thedecoding device decodes a GOS having a layer structure in one of thedirections in a world that has been set in accordance with themagnification or the intended use, preferentially from the bottom layer.

The encoding device changes the accuracy of extracting keypoints, theaccuracy of recognizing objects, or the size of spatial regions, etc.included in a SPC, depending on whether an object is an interior objector an exterior object. Note that the encoding device and the decodingdevice encode or decode an interior GOS and an exterior GOS having closecoordinates in a manner that these GOSs come adjacent to each other in aworld, and associate their identifiers with each other for encoding anddecoding.

Embodiment 2

When using encoded data of a point cloud in an actual device or service,it is desirable that necessary information be transmitted/received inaccordance with the intended use to reduce the network bandwidth.However, there has been no such functionality in the structure ofencoding three-dimensional data, nor an encoding method therefor.

The present embodiment describes a three-dimensional data encodingmethod and a three-dimensional data encoding device for providing thefunctionality of transmitting/receiving only necessary information inencoded data of a three-dimensional point cloud in accordance with theintended use, as well as a three-dimensional data decoding method and athree-dimensional data decoding device for decoding such encoded data.

A voxel (VXL) with a feature greater than or equal to a given amount isdefined as a feature voxel (FVXL), and a world (WLD) constituted byFVXLs is defined as a sparse world (SWLD). FIG. 11 is a diagram showingexample structures of a sparse world and a world. A SWLD includes:FGOSs, each being a GOS constituted by FVXLs; FSPCs, each being a SPCconstituted by FVXLs; and FVLMs, each being a VLM constituted by FVXLs.The data structure and prediction structure of a FGOS, a FSPC, and aFVLM may be the same as those of a GOS, a SPC, and a VLM.

A feature represents the three-dimensional position information on a VXLor the visible-light information on the position of a VXL. A largenumber of features are detected especially at a corner, an edge, etc. ofa three-dimensional object. More specifically, such a feature is athree-dimensional feature or a visible-light feature as described below,but may be any feature that represents the position, luminance, or colorinformation, etc. on a VXL.

Used as three-dimensional features are signature of histograms oforientations (SHOT) features, point feature histograms (PFH) features,or point pair feature (PPF) features.

SHOT features are obtained by dividing the periphery of a VXL, andcalculating an inner product of the reference point and the normalvector of each divided region to represent the calculation result as ahistogram. SHOT features are characterized by a large number ofdimensions and high-level feature representation.

PFH features are obtained by selecting a large number of two point pairsin the vicinity of a VXL, and calculating the normal vector, etc. fromeach two point pair to represent the calculation result as a histogram.PFH features are histogram features, and thus are characterized byrobustness against a certain extent of disturbance and also high-levelfeature representation.

PPF features are obtained by using a normal vector, etc. for each twopoints of VXLs. PPF features, for which all VXLs are used, hasrobustness against occlusion.

Used as visible-light features are scale-invariant feature transform(SIFT), speeded up robust features (SURF), or histogram of orientedgradients (HOG), etc. that use information on an image such as luminancegradient information.

A SWLD is generated by calculating the above-described features of therespective VXLs in a WLD to extract FVXLs. Here, the SWLD may be updatedevery time the WLD is updated, or may be regularly updated after theelapse of a certain period of time, regardless of the timing at whichthe WLD is updated.

A SWLD may be generated for each type of features. For example,different SWLDs may be generated for the respective types of features,such as SWLD1 based on SHOT features and SWLD2 based on SIFT features sothat SWLDs are selectively used in accordance with the intended use.Also, the calculated feature of each FVXL may be held in each FVXL asfeature information.

Next, the usage of a sparse world (SWLD) will be described. A SWLDincludes only feature voxels (FVXLs), and thus its data size is smallerin general than that of a WLD that includes all VXLs.

In an application that utilizes features for a certain purpose, the useof information on a SWLD instead of a WLD reduces the time required toread data from a hard disk, as well as the bandwidth and the timerequired for data transfer over a network. For example, a WLD and a SWLDare held in a server as map information so that map information to besent is selected between the WLD and the SWLD in accordance with arequest from a client. This reduces the network bandwidth and the timerequired for data transfer. More specific examples will be describedbelow.

FIG. 12 and FIG. 13 are diagrams showing usage examples of a SWLD and aWLD. As FIG. 12 shows, when client 1, which is a vehicle-mounted device,requires map information to use it for self-location determination,client 1 sends to a server a request for obtaining map data forself-location estimation (S301). The server sends to client 1 the SWLDin response to the obtainment request (S302). Client 1 uses the receivedSWLD to determine the self-location (S303). In so doing, client 1obtains VXL information on the periphery of client 1 through variousmeans including a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras.Client 1 then estimates the self-location information from the obtainedVXL information and the SWLD. Here, the self-location informationincludes three-dimensional position information, orientation, etc. ofclient 1.

As FIG. 13 shows, when client 2, which is a vehicle-mounted device,requires map information to use it for rendering a map such as athree-dimensional map, client 2 sends to the server a request forobtaining map data for map rendering (S311). The server sends to client2 the WLD in response to the obtainment request (S312). Client 2 usesthe received WLD to render a map (S313). In so doing, client 2 uses, forexample, image client 2 has captured by a visible-light camera, etc. andthe WLD obtained from the server to create a rendering image, andrenders such created image onto a screen of a car navigation system,etc.

As described above, the server sends to a client a SWLD when thefeatures of the respective VXLs are mainly required such as in the caseof self-location estimation, and sends to a client a WLD when detailedVXL information is required such as in the case of map rendering. Thisallows for an efficient sending/receiving of map data.

Note that a client may self-judge which one of a SWLD and a WLD isnecessary, and request the server to send a SWLD or a WLD. Also, theserver may judge which one of a SWLD and a WLD to send in accordancewith the status of the client or a network.

Next, a method will be described of switching the sending/receivingbetween a sparse world (SWLD) and a world (WLD).

Whether to receive a WLD or a SWLD may be switched in accordance withthe network bandwidth. FIG. 14 is a diagram showing an example operationin such case. For example, when a low-speed network is used that limitsthe usable network bandwidth, such as in a Long-Term Evolution (LTE)environment, a client accesses the server over a low-speed network(S321), and obtains the SWLD from the server as map information (S322).Meanwhile, when a high-speed network is used that has an adequatelybroad network bandwidth, such as in a WiFi environment, a clientaccesses the server over a high-speed network (S323), and obtains theWLD from the server (S324). This enables the client to obtainappropriate map information in accordance with the network bandwidthsuch client is using.

More specifically, a client receives the SWLD over an LTE network whenin outdoors, and obtains the WLD over a WiFi network when in indoorssuch as in a facility. This enables the client to obtain more detailedmap information on indoor environment.

As described above, a client may request for a WLD or a SWLD inaccordance with the bandwidth of a network such client is using.Alternatively, the client may send to the server information indicatingthe bandwidth of a network such client is using, and the server may sendto the client data (the WLD or the SWLD) suitable for such client inaccordance with the information. Alternatively, the server may identifythe network bandwidth the client is using, and send to the client data(the WLD or the SWLD) suitable for such client.

Also, whether to receive a WLD or a SWLD may be switched in accordancewith the speed of traveling. FIG. 15 is a diagram showing an exampleoperation in such case. For example, when traveling at a high speed(S331), a client receives the SWLD from the server (S332). Meanwhile,when traveling at a low speed (S333), the client receives the WLD fromthe server (S334). This enables the client to obtain map informationsuitable to the speed, while reducing the network bandwidth. Morespecifically, when traveling on an expressway, the client receives theSWLD with a small data amount, which enables the update of rough mapinformation at an appropriate speed. Meanwhile, when traveling on ageneral road, the client receives the WLD, which enables the obtainmentof more detailed map information. As described above, the client mayrequest the server for a WLD or a SWLD in accordance with the travelingspeed of such client. Alternatively, the client may send to the serverinformation indicating the traveling speed of such client, and theserver may send to the client data (the WLD or the SWLD) suitable tosuch client in accordance with the information. Alternatively, theserver may identify the traveling speed of the client to send data (theWLD or the SWLD) suitable to such client.

Also, the client may obtain, from the server, a SWLD first, from whichthe client may obtain a WLD of an important region. For example, whenobtaining map information, the client first obtains a SWLD for rough mapinformation, from which the client narrows to a region in which featuressuch as buildings, signals, or persons appear at high frequency so thatthe client can later obtain a WLD of such narrowed region. This enablesthe client to obtain detailed information on a necessary region, whilereducing the amount of data received from the server.

The server may also create from a WLD different SWLDs for the respectiveobjects, and the client may receive SWLDs in accordance with theintended use. This reduces the network bandwidth. For example, theserver recognizes persons or cars in a WLD in advance, and creates aSWLD of persons and a SWLD of cars. The client, when wishing to obtaininformation on persons around the client, receives the SWLD of persons,and when wising to obtain information on cars, receives the SWLD ofcars. Such types of SWLDs may be distinguished by information (flag, ortype, etc.) added to the header, etc.

Next, the structure and the operation flow of the three-dimensional dataencoding device (e.g., a server) according to the present embodimentwill be described. FIG. 16 is a block diagram of three-dimensional dataencoding device 400 according to the present embodiment. FIG. 17 is aflowchart of three-dimensional data encoding processes performed bythree-dimensional data encoding device 400.

Three-dimensional data encoding device 400 shown in FIG. 16 encodesinput three-dimensional data 411, thereby generating encodedthree-dimensional data 413 and encoded three-dimensional data 414, eachbeing an encoded stream. Here, encoded three-dimensional data 413 isencoded three-dimensional data corresponding to a WLD, and encodedthree-dimensional data 414 is encoded three-dimensional datacorresponding to a SWLD. Such three-dimensional data encoding device 400includes, obtainer 401, encoding region determiner 402, SWLD extractor403, WLD encoder 404, and SWLD encoder 405.

First, as FIG. 17 shows, obtainer 401 obtains input three-dimensionaldata 411, which is point cloud data in a three-dimensional space (S401).

Next, encoding region determiner 402 determines a current spatial regionfor encoding on the basis of a spatial region in which the point clouddata is present (S402).

Next, SWLD extractor 403 defines the current spatial region as a WLD,and calculates the feature from each VXL included in the WLD. Then, SWLDextractor 403 extracts VXLs having an amount of features greater than orequal to a predetermined threshold, defines the extracted VXLs as FVXLs,and adds such FVXLs to a SWLD, thereby generating extractedthree-dimensional data 412 (S403). Stated differently, extractedthree-dimensional data 412 having an amount of features greater than orequal to the threshold is extracted from input three-dimensional data411.

Next, WLD encoder 404 encodes input three-dimensional data 411corresponding to the WLD, thereby generating encoded three-dimensionaldata 413 corresponding to the WLD (S404). In so doing, WLD encoder 404adds to the header of encoded three-dimensional data 413 informationthat distinguishes that such encoded three-dimensional data 413 is astream including a WLD.

SWLD encoder 405 encodes extracted three-dimensional data 412corresponding to the SWLD, thereby generating encoded three-dimensionaldata 414 corresponding to the SWLD (S405). In so doing, SWLD encoder 405adds to the header of encoded three-dimensional data 414 informationthat distinguishes that such encoded three-dimensional data 414 is astream including a SWLD.

Note that the process of generating encoded three-dimensional data 413and the process of generating encoded three-dimensional data 414 may beperformed in the reverse order. Also note that a part or all of theseprocesses may be performed in parallel.

A parameter “world_type” is defined, for example, as information addedto each header of encoded three-dimensional data 413 and encodedthree-dimensional data 414. world_type=0 indicates that a streamincludes a WLD, and world_type=1 indicates that a stream includes aSWLD. An increased number of values may be further assigned to define alarger number of types, e.g., world_type=2. Also, one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 mayinclude a specified flag. For example, encoded three-dimensional data414 may be assigned with a flag indicating that such stream includes aSWLD. In such a case, the decoding device can distinguish whether suchstream is a stream including a WLD or a stream including a SWLD inaccordance with the presence/absence of the flag.

Also, an encoding method used by WLD encoder 404 to encode a WLD may bedifferent from an encoding method used by SWLD encoder 405 to encode aSWLD.

For example, data of a SWLD is decimated, and thus can have a lowercorrelation with the neighboring data than that of a WLD. For thisreason, of intra prediction and inter prediction, inter prediction maybe more preferentially performed in an encoding method used for a SWLDthan in an encoding method used for a WLD.

Also, an encoding method used for a SWLD and an encoding method used fora WLD may represent three-dimensional positions differently. Forexample, three-dimensional coordinates may be used to represent thethree-dimensional positions of FVXLs in a SWLD and an octree describedbelow may be used to represent three-dimensional positions in a WLD, andvice versa.

Also, SWLD encoder 405 performs encoding in a manner that encodedthree-dimensional data 414 of a SWLD has a smaller data size than thedata size of encoded three-dimensional data 413 of a WLD. A SWLD canhave a lower inter-data correlation, for example, than that of a WLD asdescribed above. This can lead to a decreased encoding efficiency, andthus to encoded three-dimensional data 414 having a larger data sizethan the data size of encoded three-dimensional data 413 of a WLD. Whenthe data size of the resulting encoded three-dimensional data 414 islarger than the data size of encoded three-dimensional data 413 of aWLD, SWLD encoder 405 performs encoding again to re-generate encodedthree-dimensional data 414 having a reduced data size.

For example, SWLD extractor 403 re-generates extracted three-dimensionaldata 412 having a reduced number of keypoints to be extracted, and SWLDencoder 405 encodes such extracted three-dimensional data 412.Alternatively, SWLD encoder 405 may perform more coarse quantization.More coarse quantization is achieved, for example, by rounding the datain the lowermost level in an octree structure described below.

When failing to decrease the data size of encoded three-dimensional data414 of the SWLD to smaller than the data size of encodedthree-dimensional data 413 of the WLD, SWLD encoder 405 may not generateencoded three-dimensional data 414 of the SWLD. Alternatively, encodedthree-dimensional data 413 of the WLD may be copied as encodedthree-dimensional data 414 of the SWLD. Stated differently, encodedthree-dimensional data 413 of the WLD may be used as it is as encodedthree-dimensional data 414 of the SWLD.

Next, the structure and the operation flow of the three-dimensional datadecoding device (e.g., a client) according to the present embodimentwill be described. FIG. 18 is a block diagram of three-dimensional datadecoding device 500 according to the present embodiment. FIG. 19 is aflowchart of three-dimensional data decoding processes performed bythree-dimensional data decoding device 500.

Three-dimensional data decoding device 500 shown in FIG. 18 decodesencoded three-dimensional data 511, thereby generating decodedthree-dimensional data 512 or decoded three-dimensional data 513.Encoded three-dimensional data 511 here is, for example, encodedthree-dimensional data 413 or encoded three-dimensional data 414generated by three-dimensional data encoding device 400.

Such three-dimensional data decoding device 500 includes obtainer 501,header analyzer 502, WLD decoder 503, and SWLD decoder 504.

First, as FIG. 19 shows, obtainer 501 obtains encoded three-dimensionaldata 511 (S501). Next, header analyzer 502 analyzes the header ofencoded three-dimensional data 511 to identify whether encodedthree-dimensional data 511 is a stream including a WLD or a streamincluding a SWLD (S502). For example, the above-described parameterworld_type is referred to in making such identification.

When encoded three-dimensional data 511 is a stream including a WLD (Yesin S503), WLD decoder 503 decodes encoded three-dimensional data 511,thereby generating decoded three-dimensional data 512 of the WLD (S504).Meanwhile, when encoded three-dimensional data 511 is a stream includinga SWLD (No in S503), SWLD decoder 504 decodes encoded three-dimensionaldata 511, thereby generating decoded three-dimensional data 513 of theSWLD (S505).

Also, as in the case of the encoding device, a decoding method used byWLD decoder 503 to decode a WLD may be different from a decoding methodused by SWLD decoder 504 to decode a SWLD. For example, of intraprediction and inter prediction, inter prediction may be morepreferentially performed in a decoding method used for a SWLD than in adecoding method used for a WLD.

Also, a decoding method used for a SWLD and a decoding method used for aWLD may represent three-dimensional positions differently. For example,three-dimensional coordinates may be used to represent thethree-dimensional positions of FVXLs in a SWLD and an octree describedbelow may be used to represent three-dimensional positions in a WLD, andvice versa.

Next, an octree representation will be described, which is a method ofrepresenting three-dimensional positions. VXL data included inthree-dimensional data is converted into an octree structure beforeencoded. FIG. 20 is a diagram showing example VXLs in a WLD. FIG. 21 isa diagram showing an octree structure of the WLD shown in FIG. 20. Anexample shown in FIG. 20 illustrates three VXLs 1 to 3 that includepoint clouds (hereinafter referred to as effective VXLs). As FIG. 21shows, the octree structure is made of nodes and leaves. Each node has amaximum of eight nodes or leaves. Each leaf has VXL information. Here,of the leaves shown in FIG. 21, leaf 1, leaf 2, and leaf 3 representVXL1, VXL2, and VXL3 shown in FIG. 20, respectively.

More specifically, each node and each leaf correspond to athree-dimensional position. Node 1 corresponds to the entire block shownin FIG. 20. The block that corresponds to node 1 is divided into eightblocks. Of these eight blocks, blocks including effective VXLs are setas nodes, while the other blocks are set as leaves. Each block thatcorresponds to a node is further divided into eight nodes or leaves.These processes are repeated by the number of times that is equal to thenumber of levels in the octree structure. All blocks in the lowermostlevel are set as leaves.

FIG. 22 is a diagram showing an example SWLD generated from the WLDshown in FIG. 20. VXL1 and VXL2 shown in FIG. 20 are judged as FVXL1 andFVXL2 as a result of feature extraction, and thus are added to the SWLD.Meanwhile, VXL3 is not judged as a FVXL, and thus is not added to theSWLD. FIG. 23 is a diagram showing an octree structure of the SWLD shownin FIG. 22. In the octree structure shown in FIG. 23, leaf 3corresponding to VXL3 shown in FIG. 21 is deleted. Consequently, node 3shown in FIG. 21 has lost an effective VXL, and has changed to a leaf.As described above, a SWLD has a smaller number of leaves in generalthan a WLD does, and thus the encoded three-dimensional data of the SWLDis smaller than the encoded three-dimensional data of the WLD.

The following describes variations of the present embodiment.

For self-location estimation, for example, a client, being avehicle-mounted device, etc., may receive a SWLD from the server to usesuch SWLD to estimate the self-location. Meanwhile, for obstacledetection, the client may detect obstacles by use of three-dimensionalinformation on the periphery obtained by such client through variousmeans including a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras.

In general, a SWLD is less likely to include VXL data on a flat region.As such, the server may hold a subsample world (subWLD) obtained bysubsampling a WLD for detection of static obstacles, and send to theclient the SWLD and the subWLD. This enables the client to performself-location estimation and obstacle detection on the client's part,while reducing the network bandwidth.

When the client renders three-dimensional map data at a high speed, mapinformation having a mesh structure is more useful in some cases. Assuch, the server may generate a mesh from a WLD to hold it beforehand asa mesh world (MWLD). For example, when wishing to perform coarsethree-dimensional rendering, the client receives a MWLD, and whenwishing to perform detailed three-dimensional rendering, the clientreceives a WLD. This reduces the network bandwidth.

In the above description, the server sets, as FVXLs, VXLs having anamount of features greater than or equal to the threshold, but theserver may calculate FVXLs by a different method. For example, theserver may judge that a VXL, a VLM, a SPC, or a GOS that constitutes asignal, or an intersection, etc. as necessary for self-locationestimation, driving assist, or self-driving, etc., and incorporate suchVXL, VLM, SPC, or GOS into a SWLD as a FVXL, a FVLM, a FSPC, or a FGOS.Such judgment may be made manually. Also, FVXLs, etc. that have been seton the basis of an amount of features may be added to FVXLs, etc.obtained by the above method. Stated differently, SWLD extractor 403 mayfurther extract, from input three-dimensional data 411, datacorresponding to an object having a predetermined attribute as extractedthree-dimensional data 412.

Also, that a VXL, a VLM, a SPC, or a GOS is necessary for such intendedusage may be labeled separately from the features. The server mayseparately hold, as an upper layer of a SWLD (e.g., a lane world), FVXLsof a signal or an intersection, etc. necessary for self-locationestimation, driving assist, or self-driving, etc.

The server may also add an attribute to VXLs in a WLD on a random accessbasis or on a predetermined unit basis. An attribute, for example,includes information indicating whether VXLs are necessary forself-location estimation, or information indicating whether VXLs areimportant as traffic information such as a signal, or an intersection,etc. An attribute may also include a correspondence between VXLs andfeatures (intersection, or road, etc.) in lane information (geographicdata files (GDF), etc.).

A method as described below may be used to update a WLD or a SWLD.

Update information indicating changes, etc. in a person, a roadwork, ora tree line (for trucks) is uploaded to the server as point clouds ormeta data. The server updates a WLD on the basis of such uploadedinformation, and then updates a SWLD by use of the updated WLD.

The client, when detecting a mismatch between the three-dimensionalinformation such client has generated at the time of self-locationestimation and the three-dimensional information received from theserver, may send to the server the three-dimensional information suchclient has generated, together with an update notification. In such acase, the server updates the SWLD by use of the WLD. When the SWLD isnot to be updated, the server judges that the WLD itself is old.

In the above description, information that distinguishes whether anencoded stream is that of a WLD or a SWLD is added as header informationof the encoded stream. However, when there are many types of worlds suchas a mesh world and a lane world, information that distinguishes thesetypes of the worlds may be added to header information. Also, when thereare many SWLDs with different amounts of features, information thatdistinguishes the respective SWLDs may be added to header information.

In the above description, a SWLD is constituted by FVXLs, but a SWLD mayinclude VXLs that have not been judged as FVXLs. For example, a SWLD mayinclude an adjacent VXL used to calculate the feature of a FVXL. Thisenables the client to calculate the feature of a FVXL when receiving aSWLD, even in the case where feature information is not added to eachFVXL of the SWLD. In such a case, the SWLD may include information thatdistinguishes whether each VXL is a FVXL or a VXL.

As described above, three-dimensional data encoding device 400 extracts,from input three-dimensional data 411 (first three-dimensional data),extracted three-dimensional data 412 (second three-dimensional data)having an amount of a feature greater than or equal to a threshold, andencodes extracted three-dimensional data 412 to generate encodedthree-dimensional data 414 (first encoded three-dimensional data).

This three-dimensional data encoding device 400 generates encodedthree-dimensional data 414 that is obtained by encoding data having anamount of a feature greater than or equal to the threshold. This reducesthe amount of data compared to the case where input three-dimensionaldata 411 is encoded as it is. Three-dimensional data encoding device 400is thus capable of reducing the amount of data to be transmitted.

Three-dimensional data encoding device 400 further encodes inputthree-dimensional data 411 to generate encoded three-dimensional data413 (second encoded three-dimensional data).

This three-dimensional data encoding device 400 enables selectivetransmission of encoded three-dimensional data 413 and encodedthree-dimensional data 414, in accordance, for example, with theintended use, etc.

Also, extracted three-dimensional data 412 is encoded by a firstencoding method, and input three-dimensional data 411 is encoded by asecond encoding method different from the first encoding method.

This three-dimensional data encoding device 400 enables the use of anencoding method suitable for each of input three-dimensional data 411and extracted three-dimensional data 412.

Also, of intra prediction and inter prediction, the inter prediction ismore preferentially performed in the first encoding method than in thesecond encoding method.

This three-dimensional data encoding device 400 enables inter predictionto be more preferentially performed on extracted three-dimensional data412 in which adjacent data items are likely to have low correlation.

Also, the first encoding method and the second encoding method representthree-dimensional positions differently. For example, the secondencoding method represents three-dimensional positions by octree, andthe first encoding method represents three-dimensional positions bythree-dimensional coordinates.

This three-dimensional data encoding device 400 enables the use of amore suitable method to represent the three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items (the number of VXLs or FVXLs) included.

Also, at least one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 includes an identifier indicating whether theencoded three-dimensional data is encoded three-dimensional dataobtained by encoding input three-dimensional data 411 or encodedthree-dimensional data obtained by encoding part of inputthree-dimensional data 411. Stated differently, such identifierindicates whether the encoded three-dimensional data is encodedthree-dimensional data 413 of a WLD or encoded three-dimensional data414 of a SWLD.

This enables the decoding device to readily judge whether the obtainedencoded three-dimensional data is encoded three-dimensional data 413 orencoded three-dimensional data 414.

Also, three-dimensional data encoding device 400 encodes extractedthree-dimensional data 412 in a manner that encoded three-dimensionaldata 414 has a smaller data amount than a data amount of encodedthree-dimensional data 413.

This three-dimensional data encoding device 400 enables encodedthree-dimensional data 414 to have a smaller data amount than the dataamount of encoded three-dimensional data 413.

Also, three-dimensional data encoding device 400 further extracts datacorresponding to an object having a predetermined attribute from inputthree-dimensional data 411 as extracted three-dimensional data 412. Theobject having a predetermined attribute is, for example, an objectnecessary for self-location estimation, driving assist, or self-driving,etc., or more specifically, a signal, an intersection, etc.

This three-dimensional data encoding device 400 is capable of generatingencoded three-dimensional data 414 that includes data required by thedecoding device.

Also, three-dimensional data encoding device 400 (server) further sends,to a client, one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 in accordance with a status of the client.

This three-dimensional data encoding device 400 is capable of sendingappropriate data in accordance with the status of the client.

Also, the status of the client includes one of a communication condition(e.g., network bandwidth) of the client and a traveling speed of theclient.

Also, three-dimensional data encoding device 400 further sends, to aclient, one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 in accordance with a request from the client.

This three-dimensional data encoding device 400 is capable of sendingappropriate data in accordance with the request from the client.

Also, three-dimensional data decoding device 500 according to thepresent embodiment decodes encoded three-dimensional data 413 or encodedthree-dimensional data 414 generated by three-dimensional data encodingdevice 400 described above.

Stated differently, three-dimensional data decoding device 500 decodes,by a first decoding method, encoded three-dimensional data 414 obtainedby encoding extracted three-dimensional data 412 having an amount of afeature greater than or equal to a threshold, extractedthree-dimensional data 412 having been extracted from inputthree-dimensional data 411. Three-dimensional data decoding device 500also decodes, by a second decoding method, encoded three-dimensionaldata 413 obtained by encoding input three-dimensional data 411, thesecond decoding method being different from the first decoding method.

This three-dimensional data decoding device 500 enables selectivereception of encoded three-dimensional data 414 obtained by encodingdata having an amount of a feature greater than or equal to thethreshold and encoded three-dimensional data 413, in accordance, forexample, with the intended use, etc. Three-dimensional data decodingdevice 500 is thus capable of reducing the amount of data to betransmitted. Such three-dimensional data decoding device 500 furtherenables the use of a decoding method suitable for each of inputthree-dimensional data 411 and extracted three-dimensional data 412.

Also, of intra prediction and inter prediction, the inter prediction ismore preferentially performed in the first decoding method than in thesecond decoding method.

This three-dimensional data decoding device 500 enables inter predictionto be more preferentially performed on the extracted three-dimensionaldata in which adjacent data items are likely to have low correlation.

Also, the first decoding method and the second decoding method representthree-dimensional positions differently. For example, the seconddecoding method represents three-dimensional positions by octree, andthe first decoding method represents three-dimensional positions bythree-dimensional coordinates.

This three-dimensional data decoding device 500 enables the use of amore suitable method to represent the three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items (the number of VXLs or FVXLs) included.

Also, at least one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 includes an identifier indicating whether theencoded three-dimensional data is encoded three-dimensional dataobtained by encoding input three-dimensional data 411 or encodedthree-dimensional data obtained by encoding part of inputthree-dimensional data 411. Three-dimensional data decoding device 500refers to such identifier in identifying between encodedthree-dimensional data 413 and encoded three-dimensional data 414.

This three-dimensional data decoding device 500 is capable of readilyjudging whether the obtained encoded three-dimensional data is encodedthree-dimensional data 413 or encoded three-dimensional data 414.

Three-dimensional data decoding device 500 further notifies a server ofa status of the client (three-dimensional data decoding device 500).Three-dimensional data decoding device 500 receives one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 fromthe server, in accordance with the status of the client.

This three-dimensional data decoding device 500 is capable of receivingappropriate data in accordance with the status of the client.

Also, the status of the client includes one of a communication condition(e.g., network bandwidth) of the client and a traveling speed of theclient.

Three-dimensional data decoding device 500 further makes a request ofthe server for one of encoded three-dimensional data 413 and encodedthree-dimensional data 414, and receives one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 fromthe server, in accordance with the request.

This three-dimensional data decoding device 500 is capable of receivingappropriate data in accordance with the intended use.

Embodiment 3

The present embodiment will describe a method of transmitting/receivingthree-dimensional data between vehicles. For example, thethree-dimensional data is transmitted/received between the own vehicleand the nearby vehicle.

FIG. 24 is a block diagram of three-dimensional data creation device 620according to the present embodiment. Such three-dimensional datacreation device 620, which is included, for example, in the own vehicle,mergers first three-dimensional data 632 created by three-dimensionaldata creation device 620 with the received second three-dimensional data635, thereby creating third three-dimensional data 636 having a higherdensity.

Such three-dimensional data creation device 620 includesthree-dimensional data creator 621, request range determiner 622,searcher 623, receiver 624, decoder 625, and merger 626.

First, three-dimensional data creator 621 creates firstthree-dimensional data 632 by use of sensor information 631 detected bythe sensor included in the own vehicle. Next, request range determiner622 determines a request range, which is the range of athree-dimensional space, the data on which is insufficient in thecreated first three-dimensional data 632.

Next, searcher 623 searches for the nearby vehicle having thethree-dimensional data of the request range, and sends request rangeinformation 633 indicating the request range to nearby vehicle 601having been searched out (S623). Next, receiver 624 receives encodedthree-dimensional data 634, which is an encoded stream of the requestrange, from nearby vehicle 601 (S624). Note that searcher 623 mayindiscriminately send requests to all vehicles included in a specifiedrange to receive encoded three-dimensional data 634 from a vehicle thathas responded to the request. Searcher 623 may send a request not onlyto vehicles but also to an object such as a signal and a sign, andreceive encoded three-dimensional data 634 from the object.

Next, decoder 625 decodes the received encoded three-dimensional data634, thereby obtaining second three-dimensional data 635. Next, merger626 merges first three-dimensional data 632 with secondthree-dimensional data 635, thereby creating three-dimensional data 636having a higher density.

Next, the structure and operations of three-dimensional datatransmission device 640 according to the present embodiment will bedescribed. FIG. 25 is a block diagram of three-dimensional datatransmission device 640.

Three-dimensional data transmission device 640 is included, for example,in the above-described nearby vehicle. Three-dimensional datatransmission device 640 processes fifth three-dimensional data 652created by the nearby vehicle into sixth three-dimensional data 654requested by the own vehicle, encodes sixth three-dimensional data 654to generate encoded three-dimensional data 634, and sends encodedthree-dimensional data 634 to the own vehicle.

Three-dimensional data transmission device 640 includesthree-dimensional data creator 641, receiver 642, extractor 643, encoder644, and transmitter 645.

First, three-dimensional data creator 641 creates fifththree-dimensional data 652 by use of sensor information 651 detected bythe sensor included in the nearby vehicle. Next, receiver 642 receivesrequest range information 633 from the own vehicle.

Next, extractor 643 extracts from fifth three-dimensional data 652 thethree-dimensional data of the request range indicated by request rangeinformation 633, thereby processing fifth three-dimensional data 652into sixth three-dimensional data 654. Next, encoder 644 encodes sixththree-dimensional data 654 to generate encoded three-dimensional data643, which is an encoded stream. Then, transmitter 645 sends encodedthree-dimensional data 634 to the own vehicle.

Note that although an example case is described here in which the ownvehicle includes three-dimensional data creation device 620 and thenearby vehicle includes three-dimensional data transmission device 640,each of the vehicles may include the functionality of boththree-dimensional data creation device 620 and three-dimensional datatransmission device 640.

Embodiment 4

The present embodiment describes operations performed in abnormal caseswhen self-location estimation is performed on the basis of athree-dimensional map.

A three-dimensional map is expected to find its expanded use inself-driving of a vehicle and autonomous movement, etc. of a mobileobject such as a robot and a flying object (e.g., a drone). Examplemeans for enabling such autonomous movement include a method in which amobile object travels in accordance with a three-dimensional map, whileestimating its self-location on the map (self-location estimation).

The self-location estimation is enabled by matching a three-dimensionalmap with three-dimensional information on the surrounding of the ownvehicle (hereinafter referred to as self-detected three-dimensionaldata) obtained by a sensor equipped in the own vehicle, such as arangefinder (e.g., a LiDAR) and a stereo camera to estimate the locationof the own vehicle on the three-dimensional map.

As in the case of an HD map suggested by HERE Technologies, for example,a three-dimensional map may include not only a three-dimensional pointcloud, but also two-dimensional map data such as information on theshapes of roads and intersections, or information that changes inreal-time such as information on a traffic jam and an accident. Athree-dimensional map includes a plurality of layers such as layers ofthree-dimensional data, two-dimensional data, and meta-data that changesin real-time, from among which the device can obtain or refer to onlynecessary data.

Point cloud data may be a SWLD as described above, or may include pointcloud data that is different from keypoints. The transmission/receptionof point cloud data is basically carried out in one or more randomaccess units.

A method described below is used as a method of matching athree-dimensional map with self-detected three-dimensional data. Forexample, the device compares the shapes of the point clouds in eachother's point clouds, and determines that portions having a high degreeof similarity among keypoints correspond to the same position. When thethree-dimensional map is formed by a SWLD, the device also performsmatching by comparing the keypoints that form the SWLD withthree-dimensional keypoints extracted from the self-detectedthree-dimensional data.

Here, to enable highly accurate self-location estimation, the followingneeds to be satisfied: (A) the three-dimensional map and theself-detected three-dimensional data have been already obtained; and (B)their accuracies satisfy a predetermined requirement. However, one of(A) and (B) cannot be satisfied in abnormal cases such as ones describedbelow.

1. A three-dimensional map is unobtainable over communication.

2. A three-dimensional map is not present, or a three-dimensional maphaving been obtained is corrupt.

3. A sensor of the own vehicle has trouble, or the accuracy of thegenerated self-detected three-dimensional data is inadequate due to badweather.

The following describes operations to cope with such abnormal cases. Thefollowing description illustrates an example case of a vehicle, but themethod described below is applicable to mobile objects on the whole thatare capable of autonomous movement, such as a robot and a drone.

The following describes the structure of the three-dimensionalinformation processing device and its operation according to the presentembodiment capable of coping with abnormal cases regarding athree-dimensional map or self-detected three-dimensional data. FIG. 26is a block diagram of an example structure of three-dimensionalinformation processing device 700 according to the present embodiment.

Three-dimensional information processing device 700 is equipped, forexample, in a mobile object such as a car. As shown in FIG. 26,three-dimensional information processing device 700 includesthree-dimensional map obtainer 701, self-detected data obtainer 702,abnormal case judgment unit 703, coping operation determiner 704, andoperation controller 705.

Note that three-dimensional information processing device 700 mayinclude a non-illustrated two-dimensional or one-dimensional sensor thatdetects a structural object or a mobile object around the own vehicle,such as a camera capable of obtaining two-dimensional images and asensor for one-dimensional data utilizing ultrasonic or laser.Three-dimensional information processing device 700 may also include anon-illustrated communication unit that obtains a three-dimensional mapover a mobile communication network, such as 4G and 5G, or viainter-vehicle communication or road-to-vehicle communication.

Three-dimensional map obtainer 701 obtains three-dimensional map 711 ofthe surroundings of the traveling route. For example, three-dimensionalmap obtainer 701 obtains three-dimensional map 711 over a mobilecommunication network, or via inter-vehicle communication orroad-to-vehicle communication.

Next, self-detected data obtainer 702 obtains self-detectedthree-dimensional data 712 on the basis of sensor information. Forexample, self-detected data obtainer 702 generates self-detectedthree-dimensional data 712 on the basis of the sensor informationobtained by a sensor equipped in the own vehicle.

Next, abnormal case judgment unit 703 conducts a predetermined check ofat least one of obtained three-dimensional map 711 and self-detectedthree-dimensional data 712 to detect an abnormal case. Stateddifferently, abnormal case judgment unit 703 judges whether at least oneof obtained three-dimensional map 711 and self-detectedthree-dimensional data 712 is abnormal.

When the abnormal case is detected, coping operation determiner 704determines a coping operation to cope with such abnormal case. Next,operation controller 705 controls the operation of each of theprocessing units necessary to perform the coping operation.

Meanwhile, when no abnormal case is detected, three-dimensionalinformation processing device 700 terminates the process.

Also, three-dimensional information processing device 700 estimates thelocation of the vehicle equipped with three-dimensional informationprocessing device 700, using three-dimensional map 711 and self-detectedthree-dimensional data 712. Next, three-dimensional informationprocessing device 700 performs the automatic operation of the vehicle byuse of the estimated location of the vehicle.

As described above, three-dimensional information processing device 700obtains, via a communication channel, map data (three-dimensional map711) that includes first three-dimensional position information. Thefirst three-dimensional position information includes, for example, aplurality of random access units, each of which is an assembly of atleast one subspace and is individually decodable, the at least onesubspace having three-dimensional coordinates information and serving asa unit in which each of the plurality of random access units is encoded.The first three-dimensional position information is, for example, data(SWLD) obtained by encoding keypoints, each of which has an amount of athree-dimensional feature greater than or equal to a predeterminedthreshold.

Three-dimensional information processing device 700 also generatessecond three-dimensional position information (self-detectedthree-dimensional data 712) from information detected by a sensor.Three-dimensional information processing device 700 then judges whetherone of the first three-dimensional position information and the secondthree-dimensional position information is abnormal by performing, on oneof the first three-dimensional position information and the secondthree-dimensional position information, a process of judging whether anabnormality is present.

Three-dimensional information processing device 700 determines a copingoperation to cope with the abnormality when one of the firstthree-dimensional position information and the second three-dimensionalposition information is judged to be abnormal. Three-dimensionalinformation processing device 700 then executes a control that isrequired to perform the coping operation.

This structure enables three-dimensional information processing device700 to detect an abnormality regarding one of the firstthree-dimensional position information and the second three-dimensionalposition information, and to perform a coping operation therefor.

Embodiment 5

The present embodiment describes a method, etc. of transmittingthree-dimensional data to a following vehicle.

FIG. 27 is a block diagram of an exemplary structure ofthree-dimensional data creation device 810 according to the presentembodiment. Such three-dimensional data creation device 810 is equipped,for example, in a vehicle. Three-dimensional data creation device 810transmits and receives three-dimensional data to and from an externalcloud-based traffic monitoring system, a preceding vehicle, or afollowing vehicle, and creates and stores three-dimensional data.

Three-dimensional data creation device 810 includes data receiver 811,communication unit 812, reception controller 813, format converter 814,a plurality of sensors 815, three-dimensional data creator 816,three-dimensional data synthesizer 817, three-dimensional data storage818, communication unit 819, transmission controller 820, formatconverter 821, and data transmitter 822.

Data receiver 811 receives three-dimensional data 831 from a cloud-basedtraffic monitoring system or a preceding vehicle. Three-dimensional data831 includes, for example, information on a region undetectable bysensors 815 of the own vehicle, such as a point cloud, visible lightvideo, depth information, sensor position information, and speedinformation.

Communication unit 812 communicates with the cloud-based trafficmonitoring system or the preceding vehicle to transmit a datatransmission request, etc. to the cloud-based traffic monitoring systemor the preceding vehicle.

Reception controller 813 exchanges information, such as information onsupported formats, with a communications partner via communication unit812 to establish communication with the communications partner.

Format converter 814 applies format conversion, etc. onthree-dimensional data 831 received by data receiver 811 to generatethree-dimensional data 832. Format converter 814 also decompresses ordecodes three-dimensional data 831 when three-dimensional data 831 iscompressed or encoded.

A plurality of sensors 815 are a group of sensors, such as visible lightcameras and infrared cameras, that obtain information on the outside ofthe vehicle and generate sensor information 833. Sensor information 833is, for example, three-dimensional data such as a point cloud (pointcloud data), when sensors 815 are laser sensors such as LiDARs. Notethat a single sensor may serve as a plurality of sensors 815.

Three-dimensional data creator 816 generates three-dimensional data 834from sensor information 833. Three-dimensional data 834 includes, forexample, information such as a point cloud, visible light video, depthinformation, sensor position information, and speed information.

Three-dimensional data synthesizer 817 synthesizes three-dimensionaldata 834 created on the basis of sensor information 833 of the ownvehicle with three-dimensional data 832 created by the cloud-basedtraffic monitoring system or the preceding vehicle, etc., therebyforming three-dimensional data 835 of a space that includes the spaceahead of the preceding vehicle undetectable by sensors 815 of the ownvehicle.

Three-dimensional data storage 818 stores generated three-dimensionaldata 835, etc.

Communication unit 819 communicates with the cloud-based trafficmonitoring system or the following vehicle to transmit a datatransmission request, etc. to the cloud-based traffic monitoring systemor the following vehicle.

Transmission controller 820 exchanges information such as information onsupported formats with a communications partner via communication unit819 to establish communication with the communications partner.Transmission controller 820 also determines a transmission region, whichis a space of the three-dimensional data to be transmitted, on the basisof three-dimensional data formation information on three-dimensionaldata 832 generated by three-dimensional data synthesizer 817 and thedata transmission request from the communications partner.

More specifically, transmission controller 820 determines a transmissionregion that includes the space ahead of the own vehicle undetectable bya sensor of the following vehicle, in response to the data transmissionrequest from the cloud-based traffic monitoring system or the followingvehicle. Transmission controller 820 judges, for example, whether aspace is transmittable or whether the already transmitted space includesan update, on the basis of the three-dimensional data formationinformation to determine a transmission region. For example,transmission controller 820 determines, as a transmission region, aregion that is: a region specified by the data transmission request; anda region, corresponding three-dimensional data 835 of which is present.Transmission controller 820 then notifies format converter 821 of theformat supported by the communications partner and the transmissionregion.

Of three-dimensional data 835 stored in three-dimensional data storage818, format converter 821 converts three-dimensional data 836 of thetransmission region into the format supported by the receiver end togenerate three-dimensional data 837. Note that format converter 821 maycompress or encode three-dimensional data 837 to reduce the data amount.

Data transmitter 822 transmits three-dimensional data 837 to thecloud-based traffic monitoring system or the following vehicle. Suchthree-dimensional data 837 includes, for example, information on a blindspot, which is a region hidden from view of the following vehicle, suchas a point cloud ahead of the own vehicle, visible light video, depthinformation, and sensor position information.

Note that an example has been described in which format converter 814and format converter 821 perform format conversion, etc., but formatconversion may not be performed.

With the above structure, three-dimensional data creation device 810obtains, from an external device, three-dimensional data 831 of a regionundetectable by sensors 815 of the own vehicle, and synthesizesthree-dimensional data 831 with three-dimensional data 834 that is basedon sensor information 833 detected by sensors 815 of the own vehicle,thereby generating three-dimensional data 835. Three-dimensional datacreation device 810 is thus capable of generating three-dimensional dataof a range undetectable by sensors 815 of the own vehicle.

Three-dimensional data creation device 810 is also capable oftransmitting, to the cloud-based traffic monitoring system or thefollowing vehicle, etc., three-dimensional data of a space that includesthe space ahead of the own vehicle undetectable by a sensor of thefollowing vehicle, in response to the data transmission request from thecloud-based traffic monitoring system or the following vehicle.

Embodiment 6

In embodiment 5, an example is described in which a client device of avehicle or the like transmits three-dimensional data to another vehicleor a server such as a cloud-based traffic monitoring system. In thepresent embodiment, a client device transmits sensor informationobtained through a sensor to a server or a client device.

A structure of a system according to the present embodiment will firstbe described. FIG. 28 is a diagram showing the structure of atransmission/reception system of a three-dimensional map and sensorinformation according to the present embodiment. This system includesserver 901, and client devices 902A and 902B. Note that client devices902A and 902B are also referred to as client device 902 when noparticular distinction is made therebetween.

Client device 902 is, for example, a vehicle-mounted device equipped ina mobile object such as a vehicle. Server 901 is, for example, acloud-based traffic monitoring system, and is capable of communicatingwith the plurality of client devices 902.

Server 901 transmits the three-dimensional map formed by a point cloudto client device 902. Note that a structure of the three-dimensional mapis not limited to a point cloud, and may also be another structureexpressing three-dimensional data such as a mesh structure.

Client device 902 transmits the sensor information obtained by clientdevice 902 to server 901. The sensor information includes, for example,at least one of information obtained by LiDAR, a visible light image, aninfrared image, a depth image, sensor position information, or sensorspeed information.

The data to be transmitted and received between server 901 and clientdevice 902 may be compressed in order to reduce data volume, and mayalso be transmitted uncompressed in order to maintain data precision.When compressing the data, it is possible to use a three-dimensionalcompression method on the point cloud based on, for example, an octreestructure. It is possible to use a two-dimensional image compressionmethod on the visible light image, the infrared image, and the depthimage. The two-dimensional image compression method is, for example,MPEG-4 AVC or HEVC standardized by MPEG.

Server 901 transmits the three-dimensional map managed by server 901 toclient device 902 in response to a transmission request for thethree-dimensional map from client device 902. Note that server 901 mayalso transmit the three-dimensional map without waiting for thetransmission request for the three-dimensional map from client device902. For example, server 901 may broadcast the three-dimensional map toat least one client device 902 located in a predetermined space. Server901 may also transmit the three-dimensional map suited to a position ofclient device 902 at fixed time intervals to client device 902 that hasreceived the transmission request once. Server 901 may also transmit thethree-dimensional map managed by server 901 to client device 902 everytime the three-dimensional map is updated.

Client device 902 sends the transmission request for thethree-dimensional map to server 901. For example, when client device 902wants to perform the self-location estimation during traveling, clientdevice 902 transmits the transmission request for the three-dimensionalmap to server 901.

Note that in the following cases, client device 902 may send thetransmission request for the three-dimensional map to server 901. Clientdevice 902 may send the transmission request for the three-dimensionalmap to server 901 when the three-dimensional map stored by client device902 is old. For example, client device 902 may send the transmissionrequest for the three-dimensional map to server 901 when a fixed periodhas passed since the three-dimensional map is obtained by client device902.

Client device 902 may also send the transmission request for thethree-dimensional map to server 901 before a fixed time when clientdevice 902 exits a space shown in the three-dimensional map stored byclient device 902. For example, client device 902 may send thetransmission request for the three-dimensional map to server 901 whenclient device 902 is located within a predetermined distance from aboundary of the space shown in the three-dimensional map stored byclient device 902. When a movement path and a movement speed of clientdevice 902 are understood, a time when client device 902 exits the spaceshown in the three-dimensional map stored by client device 902 may bepredicted based on the movement path and the movement speed of clientdevice 902.

Client device 902 may also send the transmission request for thethree-dimensional map to server 901 when an error during alignment ofthe three-dimensional data and the three-dimensional map created fromthe sensor information by client device 902 is at least at a fixedlevel.

Client device 902 transmits the sensor information to server 901 inresponse to a transmission request for the sensor information fromserver 901. Note that client device 902 may transmit the sensorinformation to server 901 without waiting for the transmission requestfor the sensor information from server 901. For example, client device902 may periodically transmit the sensor information during a fixedperiod when client device 902 has received the transmission request forthe sensor information from server 901 once. Client device 902 maydetermine that there is a possibility of a change in thethree-dimensional map of a surrounding area of client device 902 havingoccurred, and transmit this information and the sensor information toserver 901, when the error during alignment of the three-dimensionaldata created by client device 902 based on the sensor information andthe three-dimensional map obtained from server 901 is at least at thefixed level.

Server 901 sends a transmission request for the sensor information toclient device 902. For example, server 901 receives positioninformation, such as GPS information, about client device 902 fromclient device 902. Server 901 sends the transmission request for thesensor information to client device 902 in order to generate a newthree-dimensional map, when it is determined that client device 902 isapproaching a space in which the three-dimensional map managed by server901 contains little information, based on the position information aboutclient device 902. Server 901 may also send the transmission request forthe sensor information, when wanting to (i) update the three-dimensionalmap, (ii) check road conditions during snowfall, a disaster, or thelike, or (iii) check traffic congestion conditions, accident/incidentconditions, or the like.

Client device 902 may set an amount of data of the sensor information tobe transmitted to server 901 in accordance with communication conditionsor bandwidth during reception of the transmission request for the sensorinformation to be received from server 901. Setting the amount of dataof the sensor information to be transmitted to server 901 is, forexample, increasing/reducing the data itself or appropriately selectinga compression method.

FIG. 29 is a block diagram showing an example structure of client device902. Client device 902 receives the three-dimensional map formed by apoint cloud and the like from server 901, and estimates a self-locationof client device 902 using the three-dimensional map created based onthe sensor information of client device 902. Client device 902 transmitsthe obtained sensor information to server 901.

Client device 902 includes data receiver 1011, communication unit 1012,reception controller 1013, format converter 1014, sensors 1015,three-dimensional data creator 1016, three-dimensional image processor1017, three-dimensional data storage 1018, format converter 1019,communication unit 1020, transmission controller 1021, and datatransmitter 1022.

Data receiver 1011 receives three-dimensional map 1031 from server 901.Three-dimensional map 1031 is data that includes a point cloud such as aWLD or a SWLD. Three-dimensional map 1031 may include compressed data oruncompressed data.

Communication unit 1012 communicates with server 901 and transmits adata transmission request (e.g. transmission request forthree-dimensional map) to server 901.

Reception controller 1013 exchanges information, such as information onsupported formats, with a communications partner via communication unit1012 to establish communication with the communications partner.

Format converter 1014 performs a format conversion and the like onthree-dimensional map 1031 received by data receiver 1011 to generatethree-dimensional map 1032. Format converter 1014 also performs adecompression or decoding process when three-dimensional map 1031 iscompressed or encoded. Note that format converter 1014 does not performthe decompression or decoding process when three-dimensional map 1031 isuncompressed data.

Sensors 815 are a group of sensors, such as LiDARs, visible lightcameras, infrared cameras, or depth sensors that obtain informationabout the outside of a vehicle equipped with client device 902, andgenerate sensor information 1033. Sensor information 1033 is, forexample, three-dimensional data such as a point cloud (point cloud data)when sensors 1015 are laser sensors such as LiDARs. Note that a singlesensor may serve as sensors 1015.

Three-dimensional data creator 1016 generates three-dimensional data1034 of a surrounding area of the own vehicle based on sensorinformation 1033. For example, three-dimensional data creator 1016generates point cloud data with color information on the surroundingarea of the own vehicle using information obtained by LiDAR and visiblelight video obtained by a visible light camera.

Three-dimensional image processor 1017 performs a self-locationestimation process and the like of the own vehicle, using (i) thereceived three-dimensional map 1032 such as a point cloud, and (ii)three-dimensional data 1034 of the surrounding area of the own vehiclegenerated using sensor information 1033. Note that three-dimensionalimage processor 1017 may generate three-dimensional data 1035 about thesurroundings of the own vehicle by merging three-dimensional map 1032and three-dimensional data 1034, and may perform the self-locationestimation process using the created three-dimensional data 1035.

Three-dimensional data storage 1018 stores three-dimensional map 1032,three-dimensional data 1034, three-dimensional data 1035, and the like.

Format converter 1019 generates sensor information 1037 by convertingsensor information 1033 to a format supported by a receiver end. Notethat format converter 1019 may reduce the amount of data by compressingor encoding sensor information 1037. Format converter 1019 may omit thisprocess when format conversion is not necessary. Format converter 1019may also control the amount of data to be transmitted in accordance witha specified transmission range.

Communication unit 1020 communicates with server 901 and receives a datatransmission request (transmission request for sensor information) andthe like from server 901.

Transmission controller 1021 exchanges information, such as informationon supported formats, with a communications partner via communicationunit 1020 to establish communication with the communications partner.

Data transmitter 1022 transmits sensor information 1037 to server 901.Sensor information 1037 includes, for example, information obtainedthrough sensors 1015, such as information obtained by LiDAR, a luminanceimage obtained by a visible light camera, an infrared image obtained byan infrared camera, a depth image obtained by a depth sensor, sensorposition information, and sensor speed information.

A structure of server 901 will be described next. FIG. 30 is a blockdiagram showing an example structure of server 901. Server 901 transmitssensor information from client device 902 and creates three-dimensionaldata based on the received sensor information. Server 901 updates thethree-dimensional map managed by server 901 using the createdthree-dimensional data. Server 901 transmits the updatedthree-dimensional map to client device 902 in response to a transmissionrequest for the three-dimensional map from client device 902.

Server 901 includes data receiver 1111, communication unit 1112,reception controller 1113, format converter 1114, three-dimensional datacreator 1116, three-dimensional data merger 1117, three-dimensional datastorage 1118, format converter 1119, communication unit 1120,transmission controller 1121, and data transmitter 1122.

Data receiver 1111 receives sensor information 1037 from client device902. Sensor information 1037 includes, for example, information obtainedby LiDAR, a luminance image obtained by a visible light camera, aninfrared image obtained by an infrared camera, a depth image obtained bya depth sensor, sensor position information, sensor speed information,and the like.

Communication unit 1112 communicates with client device 902 andtransmits a data transmission request (e.g. transmission request forsensor information) and the like to client device 902.

Reception controller 1113 exchanges information, such as information onsupported formats, with a communications partner via communication unit1112 to establish communication with the communications partner.

Format converter 1114 generates sensor information 1132 by performing adecompression or decoding process when received sensor information 1037is compressed or encoded. Note that format converter 1114 does notperform the decompression or decoding process when sensor information1037 is uncompressed data.

Three-dimensional data creator 1116 generates three-dimensional data1134 of a surrounding area of client device 902 based on sensorinformation 1132. For example, three-dimensional data creator 1116generates point cloud data with color information on the surroundingarea of client device 902 using information obtained by LiDAR andvisible light video obtained by a visible light camera.

Three-dimensional data merger 1117 updates three-dimensional map 1135 bymerging three-dimensional data 1134 created based on sensor information1132 with three-dimensional map 1135 managed by server 901.

Three-dimensional data storage 1118 stores three-dimensional map 1135and the like.

Format converter 1119 generates three-dimensional map 1031 by convertingthree-dimensional map 1135 to a format supported by the receiver end.Note that format converter 1119 may reduce the amount of data bycompressing or encoding three-dimensional map 1135. Format converter1119 may omit this process when format conversion is not necessary.Format converter 1119 may also control the amount of data to betransmitted in accordance with a specified transmission range.

Communication unit 1120 communicates with client device 902 and receivesa data transmission request (transmission request for three-dimensionalmap) and the like from client device 902.

Transmission controller 1121 exchanges information, such as informationon supported formats, with a communications partner via communicationunit 1120 to establish communication with the communications partner.

Data transmitter 1122 transmits three-dimensional map 1031 to clientdevice 902. Three-dimensional map 1031 is data that includes a pointcloud such as a WLD or a SWLD. Three-dimensional map 1031 may includeone of compressed data and uncompressed data.

An operational flow of client device 902 will be described next. FIG. 31is a flowchart of an operation when client device 902 obtains thethree-dimensional map.

Client device 902 first requests server 901 to transmit thethree-dimensional map (point cloud, etc.) (S1001). At this point, byalso transmitting the position information about client device 902obtained through GPS and the like, client device 902 may also requestserver 901 to transmit a three-dimensional map relating to this positioninformation.

Client device 902 next receives the three-dimensional map from server901 (S1002). When the received three-dimensional map is compressed data,client device 902 decodes the received three-dimensional map andgenerates an uncompressed three-dimensional map (S1003).

Client device 902 next creates three-dimensional data 1034 of thesurrounding area of client device 902 using sensor information 1033obtained by sensors 1015 (S1004). Client device 902 next estimates theself-location of client device 902 using three-dimensional map 1032received from server 901 and three-dimensional data 1034 created usingsensor information 1033 (S1005).

FIG. 32 is a flowchart of an operation when client device 902 transmitsthe sensor information. Client device 902 first receives a transmissionrequest for the sensor information from server 901 (S1011). Clientdevice 902 that has received the transmission request transmits sensorinformation 1037 to server 901 (S1012). Note that client device 902 maygenerate sensor information 1037 by compressing each piece ofinformation using a compression method suited to each piece ofinformation, when sensor information 1033 includes a plurality of piecesof information obtained by sensors 1015.

An operational flow of server 901 will be described next. FIG. 33 is aflowchart of an operation when server 901 obtains the sensorinformation. Server 901 first requests client device 902 to transmit thesensor information (S1021). Server 901 next receives sensor information1037 transmitted from client device 902 in accordance with the request(S1022). Server 901 next creates three-dimensional data 1134 using thereceived sensor information 1037 (S1023). Server 901 next reflects thecreated three-dimensional data 1134 in three-dimensional map 1135(S1024).

FIG. 34 is a flowchart of an operation when server 901 transmits thethree-dimensional map. Server 901 first receives a transmission requestfor the three-dimensional map from client device 902 (S1031). Server 901that has received the transmission request for the three-dimensional maptransmits the three-dimensional map to client device 902 (S1032). Atthis point, server 901 may extract a three-dimensional map of a vicinityof client device 902 along with the position information about clientdevice 902, and transmit the extracted three-dimensional map. Server 901may compress the three-dimensional map formed by a point cloud using,for example, an octree structure compression method, and transmit thecompressed three-dimensional map.

Hereinafter, variations of the present embodiment will be described.

Server 901 creates three-dimensional data 1134 of a vicinity of aposition of client device 902 using sensor information 1037 receivedfrom client device 902. Server 901 next calculates a difference betweenthree-dimensional data 1134 and three-dimensional map 1135, by matchingthe created three-dimensional data 1134 with three-dimensional map 1135of the same area managed by server 901. Server 901 determines that atype of anomaly has occurred in the surrounding area of client device902, when the difference is greater than or equal to a predeterminedthreshold. For example, it is conceivable that a large difference occursbetween three-dimensional map 1135 managed by server 901 andthree-dimensional data 1134 created based on sensor information 1037,when land subsidence and the like occurs due to a natural disaster suchas an earthquake.

Sensor information 1037 may include information indicating at least oneof a sensor type, a sensor performance, and a sensor model number.Sensor information 1037 may also be appended with a class ID and thelike in accordance with the sensor performance. For example, when sensorinformation 1037 is obtained by LiDAR, it is conceivable to assignidentifiers to the sensor performance. A sensor capable of obtaininginformation with precision in units of several millimeters is class 1, asensor capable of obtaining information with precision in units ofseveral centimeters is class 2, and a sensor capable of obtaininginformation with precision in units of several meters is class 3. Server901 may estimate sensor performance information and the like from amodel number of client device 902. For example, when client device 902is equipped in a vehicle, server 901 may determine sensor specificationinformation from a type of the vehicle. In this case, server 901 mayobtain information on the type of the vehicle in advance, and theinformation may also be included in the sensor information. Server 901may change a degree of correction with respect to three-dimensional data1134 created using sensor information 1037, using obtained sensorinformation 1037. For example, when the sensor performance is high inprecision (class 1), server 901 does not correct three-dimensional data1134. When the sensor performance is low in precision (class 3), server901 corrects three-dimensional data 1134 in accordance with theprecision of the sensor. For example, server 901 increases the degree(intensity) of correction with a decrease in the precision of thesensor.

Server 901 may simultaneously send the transmission request for thesensor information to the plurality of client devices 902 in a certainspace. Server 901 does not need to use all of the sensor information forcreating three-dimensional data 1134 and may, for example, select sensorinformation to be used in accordance with the sensor performance, whenhaving received a plurality of pieces of sensor information from theplurality of client devices 902. For example, when updatingthree-dimensional map 1135, server 901 may select high-precision sensorinformation (class 1) from among the received plurality of pieces ofsensor information, and create three-dimensional data 1134 using theselected sensor information.

Server 901 is not limited to only being a server such as a cloud-basedtraffic monitoring system, and may also be another (vehicle-mounted)client device. FIG. 35 is a diagram of a system structure in this case.

For example, client device 902C sends a transmission request for sensorinformation to client device 902A located nearby, and obtains the sensorinformation from client device 902A. Client device 902C then createsthree-dimensional data using the obtained sensor information of clientdevice 902A, and updates a three-dimensional map of client device 902C.This enables client device 902C to generate a three-dimensional map of aspace that can be obtained from client device 902A, and fully utilizethe performance of client device 902C. For example, such a case isconceivable when client device 902C has high performance.

In this case, client device 902A that has provided the sensorinformation is given rights to obtain the high-precisionthree-dimensional map generated by client device 902C. Client device902A receives the high-precision three-dimensional map from clientdevice 902C in accordance with these rights.

Server 901 may send the transmission request for the sensor informationto the plurality of client devices 902 (client device 902A and clientdevice 902B) located nearby client device 902C. When a sensor of clientdevice 902A or client device 902B has high performance, client device902C is capable of creating the three-dimensional data using the sensorinformation obtained by this high-performance sensor.

FIG. 36 is a block diagram showing a functionality structure of server901 and client device 902. Server 901 includes, for example,three-dimensional map compression/decoding processor 1201 thatcompresses and decodes the three-dimensional map and sensor informationcompression/decoding processor 1202 that compresses and decodes thesensor information.

Client device 902 includes three-dimensional map decoding processor 1211and sensor information compression processor 1212. Three-dimensional mapdecoding processor 1211 receives encoded data of the compressedthree-dimensional map, decodes the encoded data, and obtains thethree-dimensional map. Sensor information compression processor 1212compresses the sensor information itself instead of thethree-dimensional data created using the obtained sensor information,and transmits the encoded data of the compressed sensor information toserver 901. With this structure, client device 902 does not need tointernally store a processor that performs a process for compressing thethree-dimensional data of the three-dimensional map (point cloud, etc.),as long as client device 902 internally stores a processor that performsa process for decoding the three-dimensional map (point cloud, etc.).This makes it possible to limit costs, power consumption, and the likeof client device 902.

As stated above, client device 902 according to the present embodimentis equipped in the mobile object, and creates three-dimensional data1034 of a surrounding area of the mobile object using sensor information1033 that is obtained through sensor 1015 equipped in the mobile objectand indicates a surrounding condition of the mobile object. Clientdevice 902 estimates a self-location of the mobile object using thecreated three-dimensional data 1034. Client device 902 transmitsobtained sensor information 1033 to server 901 or another mobile object.

This enables client device 902 to transmit sensor information 1033 toserver 901 or the like. This makes it possible to further reduce theamount of transmission data compared to when transmitting thethree-dimensional data. Since there is no need for client device 902 toperform processes such as compressing or encoding the three-dimensionaldata, it is possible to reduce the processing amount of client device902. As such, client device 902 is capable of reducing the amount ofdata to be transmitted or simplifying the structure of the device.

Client device 902 further transmits the transmission request for thethree-dimensional map to server 901 and receives three-dimensional map1031 from server 901. In the estimating of the self-location, clientdevice 902 estimates the self-location using three-dimensional data 1034and three-dimensional map 1032.

Sensor information 1034 includes at least one of information obtained bya laser sensor, a luminance image, an infrared image, a depth image,sensor position information, or sensor speed information.

Sensor information 1033 includes information that indicates aperformance of the sensor.

Client device 902 encodes or compresses sensor information 1033, and inthe transmitting of the sensor information, transmits sensor information1037 that has been encoded or compressed to server 901 or another mobileobject 902. This enables client device 902 to reduce the amount of datato be transmitted.

For example, client device 902 includes a processor and memory. Theprocessor performs the above processes using the memory.

Server 901 according to the present embodiment is capable ofcommunicating with client device 902 equipped in the mobile object, andreceives sensor information 1037 that is obtained through sensor 1015equipped in the mobile object and indicates a surrounding condition ofthe mobile object. Server 901 creates three-dimensional data 1134 of asurrounding area of the mobile object using received sensor information1037.

With this, server 901 creates three-dimensional data 1134 using sensorinformation 1037 transmitted from client device 902. This makes itpossible to further reduce the amount of transmission data compared towhen client device 902 transmits the three-dimensional data. Since thereis no need for client device 902 to perform processes such ascompressing or encoding the three-dimensional data, it is possible toreduce the processing amount of client device 902. As such, server 901is capable of reducing the amount of data to be transmitted orsimplifying the structure of the device.

Server 901 further transmits a transmission request for the sensorinformation to client device 902.

Server 901 further updates three-dimensional map 1135 using the createdthree-dimensional data 1134, and transmits three-dimensional map 1135 toclient device 902 in response to the transmission request forthree-dimensional map 1135 from client device 902.

Sensor information 1037 includes at least one of information obtained bya laser sensor, a luminance image, an infrared image, a depth image,sensor position information, or sensor speed information.

Sensor information 1037 includes information that indicates aperformance of the sensor.

Server 901 further corrects the three-dimensional data in accordancewith the performance of the sensor. This enables the three-dimensionaldata creation method to improve the quality of the three-dimensionaldata.

In the receiving of the sensor information, server 901 receives aplurality of pieces of sensor information 1037 received from a pluralityof client devices 902, and selects sensor information 1037 to be used inthe creating of three-dimensional data 1134, based on a plurality ofpieces of information that each indicates the performance of the sensorincluded in the plurality of pieces of sensor information 1037. Thisenables server 901 to improve the quality of three-dimensional data1134.

Server 901 decodes or decompresses received sensor information 1037, andcreates three-dimensional data 1134 using sensor information 1132 thathas been decoded or decompressed. This enables server 901 to reduce theamount of data to be transmitted.

For example, server 901 includes a processor and memory. The processorperforms the above processes using the memory.

Embodiment 7

In the present embodiment, three-dimensional data encoding and decodingmethods using an inter prediction process will be described.

FIG. 37 is a block diagram of three-dimensional data encoding device1300 according to the present embodiment. This three-dimensional dataencoding device 1300 generates an encoded bitstream (hereinafter, alsosimply referred to as bitstream) that is an encoded signal, by encodingthree-dimensional data. As illustrated in FIG. 37, three-dimensionaldata encoding device 1300 includes divider 1301, subtractor 1302,transformer 1303, quantizer 1304, inverse quantizer 1305, inversetransformer 1306, adder 1307, reference volume memory 1308, intrapredictor 1309, reference space memory 1310, inter predictor 1311,prediction controller 1312, and entropy encoder 1313.

Divider 1301 divides a plurality of volumes (VLMs) that are encodingunits of each space (SPC) included in the three-dimensional data.Divider 1301 makes an octree representation (make into an octree) ofvoxels in each volume. Note that divider 1301 may make the spaces intoan octree representation with the spaces having the same size as thevolumes. Divider 1301 may also append information (depth information,etc.) necessary for making the octree representation to a header and thelike of a bitstream.

Subtractor 1302 calculates a difference between a volume (encodingtarget volume) outputted by divider 1301 and a predicted volumegenerated through intra prediction or inter prediction, which will bedescribed later, and outputs the calculated difference to transformer1303 as a prediction residual. FIG. 38 is a diagram showing an examplecalculation of the prediction residual. Note that bit sequences of theencoding target volume and the predicted volume shown here are, forexample, position information indicating positions of three-dimensionalpoints included in the volumes.

Hereinafter, a scan order of an octree representation and voxels will bedescribed. A volume is encoded after being converted into an octreestructure (made into an octree). The octree structure includes nodes andleaves. Each node has eight nodes or leaves, and each leaf has voxel(VXL) information. FIG. 39 is a diagram showing an example structure ofa volume including voxels. FIG. 40 is a diagram showing an example ofthe volume shown in FIG. 39 having been converted into the octreestructure. Among the leaves shown in FIG. 40, leaves 1, 2, and 3respectively represent VXL 1, VXL 2, and VXL 3, and represent VXLsincluding a point cloud (hereinafter, active VXLs).

An octree is represented by, for example, binary sequences of is and 0s.For example, when giving the nodes or the active VXLs a value of 1 andeverything else a value of 0, each node and leaf is assigned with thebinary sequence shown in FIG. 40. Thus, this binary sequence is scannedin accordance with a breadth-first or a depth-first scan order. Forexample, when scanning breadth-first, the binary sequence shown in A ofFIG. 41 is obtained. When scanning depth-first, the binary sequenceshown in B of FIG. 41 is obtained. The binary sequences obtained throughthis scanning are encoded through entropy encoding, which reduces anamount of information.

Depth information in the octree representation will be described next.Depth in the octree representation is used in order to control up to howfine a granularity point cloud information included in a volume isstored. Upon setting a great depth, it is possible to reproduce thepoint cloud information to a more precise level, but an amount of datafor representing the nodes and leaves increases. Upon setting a smalldepth, however, the amount of data decreases, but some information thatthe point cloud information originally held is lost, since pieces ofpoint cloud information including different positions and differentcolors are now considered as pieces of point cloud information includingthe same position and the same color.

For example, FIG. 42 is a diagram showing an example in which the octreewith a depth of 2 shown in FIG. 40 is represented with a depth of 1. Theoctree shown in FIG. 42 has a lower amount of data than the octree shownin FIG. 40. In other words, the binarized octree shown in FIG. 42 has alower bit count than the octree shown in FIG. 40. Leaf 1 and leaf 2shown in FIG. 40 are represented by leaf 1 shown in FIG. 41. In otherwords, the information on leaf 1 and leaf 2 being in different positionsis lost.

FIG. 43 is a diagram showing a volume corresponding to the octree shownin FIG. 42. VXL 1 and VXL 2 shown in FIG. 39 correspond to VXL 12 shownin FIG. 43. In this case, three-dimensional data encoding device 1300generates color information of VXL 12 shown in FIG. 43 using colorinformation of VXL 1 and VXL 2 shown in FIG. 39. For example,three-dimensional data encoding device 1300 calculates an average value,a median, a weighted average value, or the like of the color informationof VXL 1 and VXL 2 as the color information of VXL 12. In this manner,three-dimensional data encoding device 1300 may control a reduction ofthe amount of data by changing the depth of the octree.

Three-dimensional data encoding device 1300 may set the depthinformation of the octree to units of worlds, units of spaces, or unitsof volumes. In this case, three-dimensional data encoding device 1300may append the depth information to header information of the world,header information of the space, or header information of the volume. Inall worlds, spaces, and volumes associated with different times, thesame value may be used as the depth information. In this case,three-dimensional data encoding device 1300 may append the depthinformation to header information managing the worlds associated withall times.

When the color information is included in the voxels, transformer 1303applies frequency transformation, e.g. orthogonal transformation, to aprediction residual of the color information of the voxels in thevolume. For example, transformer 1303 creates a one-dimensional array byscanning the prediction residual in a certain scan order. Subsequently,transformer 1303 transforms the one-dimensional array to a frequencydomain by applying one-dimensional orthogonal transformation to thecreated one-dimensional array. With this, when a value of the predictionresidual in the volume is similar, a value of a low-frequency componentincreases and a value of a high-frequency component decreases. As such,it is possible to more efficiently reduce a code amount in quantizer1304.

Transformer 1303 does not need to use orthogonal transformation in onedimension, but may also use orthogonal transformation in two or moredimensions. For example, transformer 1303 maps the prediction residualto a two-dimensional array in a certain scan order, and appliestwo-dimensional orthogonal transformation to the obtainedtwo-dimensional array. Transformer 1303 may select an orthogonaltransformation method to be used from a plurality of orthogonaltransformation methods. In this case, three-dimensional data encodingdevice 1300 appends, to the bitstream, information indicating whichorthogonal transformation method is used. Transformer 1303 may select anorthogonal transformation method to be used from a plurality oforthogonal transformation methods in different dimensions. In this case,three-dimensional data encoding device 1300 appends, to the bitstream,in how many dimensions the orthogonal transformation method is used.

For example, transformer 1303 matches the scan order of the predictionresidual to a scan order (breadth-first, depth-first, or the like) inthe octree in the volume. This makes it possible to reduce overhead,since information indicating the scan order of the prediction residualdoes not need to be appended to the bitstream. Transformer 1303 mayapply a scan order different from the scan order of the octree. In thiscase, three-dimensional data encoding device 1300 appends, to thebitstream, information indicating the scan order of the predictionresidual. This enables three-dimensional data encoding device 1300 toefficiently encode the prediction residual. Three-dimensional dataencoding device 1300 may append, to the bitstream, information (flag,etc.) indicating whether to apply the scan order of the octree, and mayalso append, to the bitstream, information indicating the scan order ofthe prediction residual when the scan order of the octree is notapplied.

Transformer 1303 does not only transform the prediction residual of thecolor information, and may also transform other attribute informationincluded in the voxels. For example, transformer 1303 may transform andencode information, such as reflectance information, obtained whenobtaining a point cloud through LiDAR and the like.

Transformer 1303 may skip these processes when the spaces do not includeattribute information such as color information. Three-dimensional dataencoding device 1300 may append, to the bitstream, information (flag)indicating whether to skip the processes of transformer 1303.

Quantizer 1304 generates a quantized coefficient by performingquantization using a quantization control parameter on a frequencycomponent of the prediction residual generated by transformer 1303. Withthis, the amount of information is further reduced. The generatedquantized coefficient is outputted to entropy encoder 1313. Quantizer1304 may control the quantization control parameter in units of worlds,units of spaces, or units of volumes. In this case, three-dimensionaldata encoding device 1300 appends the quantization control parameter toeach header information and the like. Quantizer 1304 may performquantization control by changing a weight per frequency component of theprediction residual. For example, quantizer 1304 may precisely quantizea low-frequency component and roughly quantize a high-frequencycomponent. In this case, three-dimensional data encoding device 1300 mayappend, to a header, a parameter expressing a weight of each frequencycomponent.

Quantizer 1304 may skip these processes when the spaces do not includeattribute information such as color information. Three-dimensional dataencoding device 1300 may append, to the bitstream, information (flag)indicating whether to skip the processes of quantizer 1304.

Inverse quantizer 1305 generates an inverse quantized coefficient of theprediction residual by performing inverse quantization on the quantizedcoefficient generated by quantizer 1304 using the quantization controlparameter, and outputs the generated inverse quantized coefficient toinverse transformer 1306.

Inverse transformer 1306 generates an inverse transformation-appliedprediction residual by applying inverse transformation on the inversequantized coefficient generated by inverse quantizer 1305. This inversetransformation-applied prediction residual does not need to completelycoincide with the prediction residual outputted by transformer 1303,since the inverse transformation-applied prediction residual is aprediction residual that is generated after the quantization.

Adder 1307 adds, to generate a reconstructed volume, (i) the inversetransformation-applied prediction residual generated by inversetransformer 1306 to (ii) a predicted volume that is generated throughintra prediction or intra prediction, which will be described later, andis used to generate a pre-quantized prediction residual. Thisreconstructed volume is stored in reference volume memory 1308 orreference space memory 1310.

Intra predictor 1309 generates a predicted volume of an encoding targetvolume using attribute information of a neighboring volume stored inreference volume memory 1308. The attribute information includes colorinformation or a reflectance of the voxels. Intra predictor 1309generates a predicted value of color information or a reflectance of theencoding target volume.

FIG. 44 is a diagram for describing an operation of intra predictor1309. For example, intra predictor 1309 generates the predicted volumeof the encoding target volume (volume idx=3) shown in FIG. 44, using aneighboring volume (volume idx=0). Volume idx here is identifierinformation that is appended to a volume in a space, and a differentvalue is assigned to each volume. An order of assigning volume idx maybe the same as an encoding order, and may also be different from theencoding order. For example, intra predictor 1309 uses an average valueof color information of voxels included in volume idx=0, which is aneighboring volume, as the predicted value of the color information ofthe encoding target volume shown in FIG. 44. In this case, a predictionresidual is generated by deducting the predicted value of the colorinformation from the color information of each voxel included in theencoding target volume. The following processes are performed bytransformer 1303 and subsequent processors with respect to thisprediction residual. In this case, three-dimensional data encodingdevice 1300 appends, to the bitstream, neighboring volume informationand prediction mode information. The neighboring volume information hereis information indicating a neighboring volume used in the prediction,and indicates, for example, volume idx of the neighboring volume used inthe prediction. The prediction mode information here indicates a modeused to generate the predicted volume. The mode is, for example, anaverage value mode in which the predicted value is generated using anaverage value of the voxels in the neighboring volume, or a median modein which the predicted value is generated using the median of the voxelsin the neighboring volume.

Intra predictor 1309 may generate the predicted volume using a pluralityof neighboring volumes. For example, in the structure shown in FIG. 44,intra predictor 1309 generates predicted volume 0 using a volume withvolume idx=0, and generates predicted volume 1 using a volume withvolume idx=1. Intra predictor 1309 then generates an average ofpredicted volume 0 and predicted volume 1 as a final predicted volume.In this case, three-dimensional data encoding device 1300 may append, tothe bitstream, a plurality of volumes idx of a plurality of volumes usedto generate the predicted volume.

FIG. 45 is a diagram schematically showing the inter prediction processaccording to the present embodiment. Inter predictor 1311 encodes (interpredicts) a space (SPC) associated with certain time T_Cur using anencoded space associated with different time T_LX. In this case, interpredictor 1311 performs an encoding process by applying a rotation andtranslation process to the encoded space associated with different timeT_LX.

Three-dimensional data encoding device 1300 appends, to the bitstream,RT information relating to a rotation and translation process suited tothe space associated with different time T_LX. Different time T_LX is,for example, time T_L0 before certain time T_Cur. At this point,three-dimensional data encoding device 1300 may append, to thebitstream, RT information RT_L0 relating to a rotation and translationprocess suited to a space associated with time T_L0.

Alternatively, different time T_LX is, for example, time T_L1 aftercertain time T_Cur. At this point, three-dimensional data encodingdevice 1300 may append, to the bitstream, RT information RT_L1 relatingto a rotation and translation process suited to a space associated withtime T_L1.

Alternatively, inter predictor 1311 encodes (bidirectional prediction)with reference to the spaces associated with time T_L0 and time T_L1that differ from each other. In this case, three-dimensional dataencoding device 1300 may append, to the bitstream, both RT informationRT_L0 and RT information RT_L1 relating to the rotation and translationprocess suited to the spaces thereof.

Note that T_L0 has been described as being before T_Cur and T_L1 asbeing after T_Cur, but are not necessarily limited thereto. For example,T_L0 and T_L1 may both be before T_Cur. T_L0 and T_L1 may also both beafter T_Cur.

Three-dimensional data encoding device 1300 may append, to thebitstream, RT information relating to a rotation and translation processsuited to spaces associated with different times, when encoding withreference to each of the spaces. For example, three-dimensional dataencoding device 1300 manages a plurality of encoded spaces to bereferred to, using two reference lists (list L0 and list L1). When afirst reference space in list L0 is L0R0, a second reference space inlist L0 is L0R1, a first reference space in list L1 is L1R0, and asecond reference space in list L1 is L1R1, three-dimensional dataencoding device 1300 appends, to the bitstream, RT information RT_L0R0of L0R0, RT information RT_L0R1 of L0R1, RT information RT_L1R0 of L1R0,and RT information RT_L1R1 of L1R1. For example, three-dimensional dataencoding device 1300 appends these pieces of RT information to a headerand the like of the bitstream.

Three-dimensional data encoding device 1300 determines whether to applyrotation and translation per reference space, when encoding withreference to reference spaces associated with different times. In thiscase, three-dimensional data encoding device 1300 may append, to headerinformation and the like of the bitstream, information (RT flag, etc.)indicating whether rotation and translation are applied per referencespace. For example, three-dimensional data encoding device 1300calculates the RT information and an Iterative Closest Point (ICP) errorvalue, using an ICP algorithm per reference space to be referred to fromthe encoding target space. Three-dimensional data encoding device 1300determines that rotation and translation do not need to be performed andsets the RT flag to OFF, when the ICP error value is lower than or equalto a predetermined fixed value. In contrast, three-dimensional dataencoding device 1300 sets the RT flag to ON and appends the RTinformation to the bitstream, when the ICP error value exceeds the abovefixed value.

FIG. 46 is a diagram showing an example syntax to be appended to aheader of the RT information and the RT flag. Note that a bit countassigned to each syntax may be decided based on a range of this syntax.For example, when eight reference spaces are included in reference listL0, 3 bits may be assigned to MaxRefSpc_10. The bit count to be assignedmay be variable in accordance with a value each syntax can be, and mayalso be fixed regardless of the value each syntax can be. When the bitcount to be assigned is fixed, three-dimensional data encoding device1300 may append this fixed bit count to other header information.

MaxRefSpc_10 shown in FIG. 46 indicates a number of reference spacesincluded in reference list L0. RT_flag_10[i] is an RT flag of referencespace i in reference list L0. When RT_flag_10[i] is 1, rotation andtranslation are applied to reference space i. When RT_flag_10[i] is 0,rotation and translation are not applied to reference space i.

R_10[i] and T_10[i] are RT information of reference space i in referencelist L0. R_10[i] is rotation information of reference space i inreference list L0. The rotation information indicates contents of theapplied rotation process, and is, for example, a rotation matrix or aquaternion. T_10[i] is translation information of reference space i inreference list L0. The translation information indicates contents of theapplied translation process, and is, for example, a translation vector.

MaxRefSpc_l1 indicates a number of reference spaces included inreference list L1. RT_flag_l1[i] is an RT flag of reference space i inreference list L1. When RT_flag_l1[i] is 1, rotation and translation areapplied to reference space i. When RT_flag_l1[i] is 0, rotation andtranslation are not applied to reference space i.

R_l1[i] and T_l1[i] are RT information of reference space i in referencelist L1. R_l1[i] is rotation information of reference space i inreference list L1. The rotation information indicates contents of theapplied rotation process, and is, for example, a rotation matrix or aquaternion. T_l1[i] is translation information of reference space i inreference list L1. The translation information indicates contents of theapplied translation process, and is, for example, a translation vector.

Inter predictor 1311 generates the predicted volume of the encodingtarget volume using information on an encoded reference space stored inreference space memory 1310. As stated above, before generating thepredicted volume of the encoding target volume, inter predictor 1311calculates RT information at an encoding target space and a referencespace using an ICP algorithm, in order to approach an overall positionalrelationship between the encoding target space and the reference space.Inter predictor 1311 then obtains reference space B by applying arotation and translation process to the reference space using thecalculated RT information. Subsequently, inter predictor 1311 generatesthe predicted volume of the encoding target volume in the encodingtarget space using information in reference space B. Three-dimensionaldata encoding device 1300 appends, to header information and the like ofthe encoding target space, the RT information used to obtain referencespace B.

In this manner, inter predictor 1311 is capable of improving precisionof the predicted volume by generating the predicted volume using theinformation of the reference space, after approaching the overallpositional relationship between the encoding target space and thereference space, by applying a rotation and translation process to thereference space. It is possible to reduce the code amount since it ispossible to limit the prediction residual. Note that an example has beendescribed in which ICP is performed using the encoding target space andthe reference space, but is not necessarily limited thereto. Forexample, inter predictor 1311 may calculate the RT information byperforming ICP using at least one of (i) an encoding target space inwhich a voxel or point cloud count is pruned, or (ii) a reference spacein which a voxel or point cloud count is pruned, in order to reduce theprocessing amount.

When the ICP error value obtained as a result of the ICP is smaller thana predetermined first threshold, i.e., when for example the positionalrelationship between the encoding target space and the reference spaceis similar, inter predictor 1311 determines that a rotation andtranslation process is not necessary, and the rotation and translationprocess does not need to be performed. In this case, three-dimensionaldata encoding device 1300 may control the overhead by not appending theRT information to the bitstream.

When the ICP error value is greater than a predetermined secondthreshold, inter predictor 1311 determines that a shape change betweenthe spaces is large, and intra prediction may be applied on all volumesof the encoding target space. Hereinafter, spaces to which intraprediction is applied will be referred to as intra spaces. The secondthreshold is greater than the above first threshold. The presentembodiment is not limited to ICP, and any type of method may be used aslong as the method calculates the RT information using two voxel sets ortwo point cloud sets.

When attribute information, e.g. shape or color information, is includedin the three-dimensional data, inter predictor 1311 searches, forexample, a volume whose attribute information, e.g. shape or colorinformation, is the most similar to the encoding target volume in thereference space, as the predicted volume of the encoding target volumein the encoding target space. This reference space is, for example, areference space on which the above rotation and translation process hasbeen performed. Inter predictor 1311 generates the predicted volumeusing the volume (reference volume) obtained through the search. FIG. 47is a diagram for describing a generating operation of the predictedvolume. When encoding the encoding target volume (volume idx=0) shown inFIG. 47 using inter prediction, inter predictor 1311 searches a volumewith a smallest prediction residual, which is the difference between theencoding target volume and the reference volume, while sequentiallyscanning the reference volume in the reference space. Inter predictor1311 selects the volume with the smallest prediction residual as thepredicted volume. The prediction residuals of the encoding target volumeand the predicted volume are encoded through the processes performed bytransformer 1303 and subsequent processors. The prediction residual hereis a difference between the attribute information of the encoding targetvolume and the attribute information of the predicted volume.Three-dimensional data encoding device 1300 appends, to the header andthe like of the bitstream, volume idx of the reference volume in thereference space, as the predicted volume.

In the example shown in FIG. 47, the reference volume with volume idx=4of reference space L0R0 is selected as the predicted volume of theencoding target volume. The prediction residuals of the encoding targetvolume and the reference volume, and reference volume idx=4 are thenencoded and appended to the bitstream.

Note that an example has been described in which the predicted volume ofthe attribute information is generated, but the same process may beapplied to the predicted volume of the position information.

Prediction controller 1312 controls whether to encode the encodingtarget volume using intra prediction or inter prediction. A modeincluding intra prediction and inter prediction is referred to here as aprediction mode. For example, prediction controller 1312 calculates theprediction residual when the encoding target volume is predicted usingintra prediction and the prediction residual when the encoding targetvolume is predicted using inter prediction as evaluation values, andselects the prediction mode whose evaluation value is smaller. Note thatprediction controller 1312 may calculate an actual code amount byapplying orthogonal transformation, quantization, and entropy encodingto the prediction residual of the intra prediction and the predictionresidual of the inter prediction, and select a prediction mode using thecalculated code amount as the evaluation value. Overhead information(reference volume idx information, etc.) aside from the predictionresidual may be added to the evaluation value. Prediction controller1312 may continuously select intra prediction when it has been decidedin advance to encode the encoding target space using intra space.

Entropy encoder 1313 generates an encoded signal (encoded bitstream) byvariable-length encoding the quantized coefficient, which is an inputfrom quantizer 1304. To be specific, entropy encoder 1313, for example,binarizes the quantized coefficient and arithmetically encodes theobtained binary signal.

A three-dimensional data decoding device that decodes the encoded signalgenerated by three-dimensional data encoding device 1300 will bedescribed next. FIG. 48 is a block diagram of three-dimensional datadecoding device 1400 according to the present embodiment. Thisthree-dimensional data decoding device 1400 includes entropy decoder1401, inverse quantizer 1402, inverse transformer 1403, adder 1404,reference volume memory 1405, intra predictor 1406, reference spacememory 1407, inter predictor 1408, and prediction controller 1409.

Entropy decoder 1401 variable-length decodes the encoded signal (encodedbitstream). For example, entropy decoder 1401 generates a binary signalby arithmetically decoding the encoded signal, and generates a quantizedcoefficient using the generated binary signal.

Inverse quantizer 1402 generates an inverse quantized coefficient byinverse quantizing the quantized coefficient inputted from entropydecoder 1401, using a quantization parameter appended to the bitstreamand the like.

Inverse transformer 1403 generates a prediction residual by inversetransforming the inverse quantized coefficient inputted from inversequantizer 1402. For example, inverse transformer 1403 generates theprediction residual by inverse orthogonally transforming the inversequantized coefficient, based on information appended to the bitstream.

Adder 1404 adds, to generate a reconstructed volume, (i) the predictionresidual generated by inverse transformer 1403 to (ii) a predictedvolume generated through intra prediction or intra prediction. Thisreconstructed volume is outputted as decoded three-dimensional data andis stored in reference volume memory 1405 or reference space memory1407.

Intra predictor 1406 generates a predicted volume through intraprediction using a reference volume in reference volume memory 1405 andinformation appended to the bitstream. To be specific, intra predictor1406 obtains neighboring volume information (e.g. volume idx) appendedto the bitstream and prediction mode information, and generates thepredicted volume through a mode indicated by the prediction modeinformation, using a neighboring volume indicated in the neighboringvolume information. Note that the specifics of these processes are thesame as the above-mentioned processes performed by intra predictor 1309,except for which information appended to the bitstream is used.

Inter predictor 1408 generates a predicted volume through interprediction using a reference space in reference space memory 1407 andinformation appended to the bitstream. To be specific, inter predictor1408 applies a rotation and translation process to the reference spaceusing the RT information per reference space appended to the bitstream,and generates the predicted volume using the rotated and translatedreference space. Note that when an RT flag is present in the bitstreamper reference space, inter predictor 1408 applies a rotation andtranslation process to the reference space in accordance with the RTflag. Note that the specifics of these processes are the same as theabove-mentioned processes performed by inter predictor 1311, except forwhich information appended to the bitstream is used.

Prediction controller 1409 controls whether to decode a decoding targetvolume using intra prediction or inter prediction. For example,prediction controller 1409 selects intra prediction or inter predictionin accordance with information that is appended to the bitstream andindicates the prediction mode to be used. Note that predictioncontroller 1409 may continuously select intra prediction when it hasbeen decided in advance to decode the decoding target space using intraspace.

Hereinafter, variations of the present embodiment will be described. Inthe present embodiment, an example has been described in which rotationand translation is applied in units of spaces, but rotation andtranslation may also be applied in smaller units. For example,three-dimensional data encoding device 1300 may divide a space intosubspaces, and apply rotation and translation in units of subspaces. Inthis case, three-dimensional data encoding device 1300 generates RTinformation per subspace, and appends the generated RT information to aheader and the like of the bitstream. Three-dimensional data encodingdevice 1300 may apply rotation and translation in units of volumes,which is an encoding unit. In this case, three-dimensional data encodingdevice 1300 generates RT information in units of encoded volumes, andappends the generated RT information to a header and the like of thebitstream. The above may also be combined. In other words,three-dimensional data encoding device 1300 may apply rotation andtranslation in large units and subsequently apply rotation andtranslation in small units. For example, three-dimensional data encodingdevice 1300 may apply rotation and translation in units of spaces, andmay also apply different rotations and translations to each of aplurality of volumes included in the obtained spaces.

In the present embodiment, an example has been described in whichrotation and translation is applied to the reference space, but is notnecessarily limited thereto. For example, three-dimensional dataencoding device 1300 may apply a scaling process and change a size ofthe three-dimensional data. Three-dimensional data encoding device 1300may also apply one or two of the rotation, translation, and scaling.When applying the processes in multiple stages and different units asstated above, a type of the processes applied in each unit may differ.For example, rotation and translation may be applied in units of spaces,and translation may be applied in units of volumes.

Note that these variations are also applicable to three-dimensional datadecoding device 1400.

As stated above, three-dimensional data encoding device 1300 accordingto the present embodiment performs the following processes. FIG. 48 is aflowchart of the inter prediction process performed by three-dimensionaldata encoding device 1300.

Three-dimensional data encoding device 1300 generates predicted positioninformation (e.g. predicted volume) using position information onthree-dimensional points included in three-dimensional reference data(e.g. reference space) associated with a time different from a timeassociated with current three-dimensional data (e.g. encoding targetspace) (S1301). To be specific, three-dimensional data encoding device1300 generates the predicted position information by applying a rotationand translation process to the position information on thethree-dimensional points included in the three-dimensional referencedata.

Note that three-dimensional data encoding device 1300 may perform arotation and translation process using a first unit (e.g. spaces), andmay perform the generating of the predicted position information using asecond unit (e.g. volumes) that is smaller than the first unit. Forexample, three-dimensional data encoding device 1300 searches a volumeamong a plurality of volumes included in the rotated and translatedreference space, whose position information differs the least from theposition information of the encoding target volume included in theencoding target space. Note that three-dimensional data encoding device1300 may perform the rotation and translation process, and thegenerating of the predicted position information in the same unit.

Three-dimensional data encoding device 1300 may generate the predictedposition information by applying (i) a first rotation and translationprocess to the position information on the three-dimensional pointsincluded in the three-dimensional reference data, and (ii) a secondrotation and translation process to the position information on thethree-dimensional points obtained through the first rotation andtranslation process, the first rotation and translation process using afirst unit (e.g. spaces) and the second rotation and translation processusing a second unit (e.g. volumes) that is smaller than the first unit.

For example, as illustrated in FIG. 41, the position information on thethree-dimensional points and the predicted position information isrepresented using an octree structure. For example, the positioninformation on the three-dimensional points and the predicted positioninformation is expressed in a scan order that prioritizes a breadth overa depth in the octree structure. For example, the position informationon the three-dimensional points and the predicted position informationis expressed in a scan order that prioritizes a depth over a breadth inthe octree structure.

As illustrated in FIG. 46, three-dimensional data encoding device 1300encodes an RT flag that indicates whether to apply the rotation andtranslation process to the position information on the three-dimensionalpoints included in the three-dimensional reference data. In other words,three-dimensional data encoding device 1300 generates the encoded signal(encoded bitstream) including the RT flag. Three-dimensional dataencoding device 1300 encodes RT information that indicates contents ofthe rotation and translation process. In other words, three-dimensionaldata encoding device 1300 generates the encoded signal (encodedbitstream) including the RT information. Note that three-dimensionaldata encoding device 1300 may encode the RT information when the RT flagindicates to apply the rotation and translation process, and does notneed to encode the RT information when the RT flag indicates not toapply the rotation and translation process.

The three-dimensional data includes, for example, the positioninformation on the three-dimensional points and the attributeinformation (color information, etc.) of each three-dimensional point.Three-dimensional data encoding device 1300 generates predictedattribute information using the attribute information of thethree-dimensional points included in the three-dimensional referencedata (S1302).

Three-dimensional data encoding device 1300 next encodes the positioninformation on the three-dimensional points included in the currentthree-dimensional data, using the predicted position information. Forexample, as illustrated in FIG. 38, three-dimensional data encodingdevice 1300 calculates differential position information, thedifferential position information being a difference between thepredicted position information and the position information on thethree-dimensional points included in the current three-dimensional data(S1303).

Three-dimensional data encoding device 1300 encodes the attributeinformation of the three-dimensional points included in the currentthree-dimensional data, using the predicted attribute information. Forexample, three-dimensional data encoding device 1300 calculatesdifferential attribute information, the differential attributeinformation being a difference between the predicted attributeinformation and the attribute information on the three-dimensionalpoints included in the current three-dimensional data (S1304).Three-dimensional data encoding device 1300 next performs transformationand quantization on the calculated differential attribute information(S1305).

Lastly, three-dimensional data encoding device 1300 encodes (e.g.entropy encodes) the differential position information and the quantizeddifferential attribute information (S1036). In other words,three-dimensional data encoding device 1300 generates the encoded signal(encoded bitstream) including the differential position information andthe differential attribute information.

Note that when the attribute information is not included in thethree-dimensional data, three-dimensional data encoding device 1300 doesnot need to perform steps S1302, S1304, and S1305. Three-dimensionaldata encoding device 1300 may also perform only one of the encoding ofthe position information on the three-dimensional points and theencoding of the attribute information of the three-dimensional points.

An order of the processes shown in FIG. 49 is merely an example and isnot limited thereto. For example, since the processes with respect tothe position information (S1301 and S1303) and the processes withrespect to the attribute information (S1302, S1304, and S1305) areseparate from one another, they may be performed in an order of choice,and a portion thereof may also be performed in parallel.

With the above, three-dimensional data encoding device 1300 according tothe present embodiment generates predicted position information usingposition information on three-dimensional points included inthree-dimensional reference data associated with a time different from atime associated with current three-dimensional data; and encodesdifferential position information, which is a difference between thepredicted position information and the position information on thethree-dimensional points included in the current three-dimensional data.This makes it possible to improve encoding efficiency since it ispossible to reduce the amount of data of the encoded signal.

Three-dimensional data encoding device 1300 according to the presentembodiment generates predicted attribute information using attributeinformation on three-dimensional points included in three-dimensionalreference data; and encodes differential attribute information, which isa difference between the predicted attribute information and theattribute information on the three-dimensional points included in thecurrent three-dimensional data. This makes it possible to improveencoding efficiency since it is possible to reduce the amount of data ofthe encoded signal.

For example, three-dimensional data encoding device 1300 includes aprocessor and memory. The processor uses the memory to perform the aboveprocesses.

FIG. 48 is a flowchart of the inter prediction process performed bythree-dimensional data decoding device 1400.

Three-dimensional data decoding device 1400 decodes (e.g. entropydecodes) the differential position information and the differentialattribute information from the encoded signal (encoded bitstream)(S1401).

Three-dimensional data decoding device 1400 decodes, from the encodedsignal, an RT flag that indicates whether to apply the rotation andtranslation process to the position information on the three-dimensionalpoints included in the three-dimensional reference data.Three-dimensional data decoding device 1400 encodes RT information thatindicates contents of the rotation and translation process. Note thatthree-dimensional data decoding device 1400 may decode the RTinformation when the RT flag indicates to apply the rotation andtranslation process, and does not need to decode the RT information whenthe RT flag indicates not to apply the rotation and translation process.

Three-dimensional data decoding device 1400 next performs inversetransformation and inverse quantization on the decoded differentialattribute information (S1402).

Three-dimensional data decoding device 1400 next generates predictedposition information (e.g. predicted volume) using the positioninformation on the three-dimensional points included in thethree-dimensional reference data (e.g. reference space) associated witha time different from a time associated with the currentthree-dimensional data (e.g. decoding target space) (S1403). To bespecific, three-dimensional data decoding device 1400 generates thepredicted position information by applying a rotation and translationprocess to the position information on the three-dimensional pointsincluded in the three-dimensional reference data.

More specifically, when the RT flag indicates to apply the rotation andtranslation process, three-dimensional data decoding device 1400 appliesthe rotation and translation process on the position information on thethree-dimensional points included in the three-dimensional referencedata indicated in the RT information. In contrast, when the RT flagindicates not to apply the rotation and translation process,three-dimensional data decoding device 1400 does not apply the rotationand translation process on the position information on thethree-dimensional points included in the three-dimensional referencedata.

Note that three-dimensional data decoding device 1400 may perform therotation and translation process using a first unit (e.g. spaces), andmay perform the generating of the predicted position information using asecond unit (e.g. volumes) that is smaller than the first unit. Notethat three-dimensional data decoding device 1400 may perform therotation and translation process, and the generating of the predictedposition information in the same unit.

Three-dimensional data decoding device 1400 may generate the predictedposition information by applying (i) a first rotation and translationprocess to the position information on the three-dimensional pointsincluded in the three-dimensional reference data, and (ii) a secondrotation and translation process to the position information on thethree-dimensional points obtained through the first rotation andtranslation process, the first rotation and translation process using afirst unit (e.g. spaces) and the second rotation and translation processusing a second unit (e.g. volumes) that is smaller than the first unit.

For example, as illustrated in FIG. 41, the position information on thethree-dimensional points and the predicted position information isrepresented using an octree structure. For example, the positioninformation on the three-dimensional points and the predicted positioninformation is expressed in a scan order that prioritizes a breadth overa depth in the octree structure. For example, the position informationon the three-dimensional points and the predicted position informationis expressed in a scan order that prioritizes a depth over a breadth inthe octree structure.

Three-dimensional data decoding device 1400 generates predictedattribute information using the attribute information of thethree-dimensional points included in the three-dimensional referencedata (S1404).

Three-dimensional data decoding device 1400 next restores the positioninformation on the three-dimensional points included in the currentthree-dimensional data, by decoding encoded position informationincluded in an encoded signal, using the predicted position information.The encoded position information here is the differential positioninformation. Three-dimensional data decoding device 1400 restores theposition information on the three-dimensional points included in thecurrent three-dimensional data, by adding the differential positioninformation to the predicted position information (S1405).

Three-dimensional data decoding device 1400 restores the attributeinformation of the three-dimensional points included in the currentthree-dimensional data, by decoding encoded attribute informationincluded in an encoded signal, using the predicted attributeinformation. The encoded attribute information here is the differentialposition information. Three-dimensional data decoding device 1400restores the attribute information on the three-dimensional pointsincluded in the current three-dimensional data, by adding thedifferential attribute information to the predicted attributeinformation (S1406).

Note that when the attribute information is not included in thethree-dimensional data, three-dimensional data decoding device 1400 doesnot need to perform steps S1402, S1404, and S1406. Three-dimensionaldata decoding device 1400 may also perform only one of the decoding ofthe position information on the three-dimensional points and thedecoding of the attribute information of the three-dimensional points.

An order of the processes shown in FIG. 50 is merely an example and isnot limited thereto. For example, since the processes with respect tothe position information (S1403 and S1405) and the processes withrespect to the attribute information (S1402, S1404, and S1406) areseparate from one another, they may be performed in an order of choice,and a portion thereof may also be performed in parallel.

Embodiment 8

In the present embodiment, a method of controlling reference when anoccupancy code is encoded will be described. It should be noted thatalthough the following mainly describes an operation of athree-dimensional data encoding device, a three-dimensional datadecoding device may perform the same process.

FIG. 51 and FIG. 52 each are a diagram illustrating a referencerelationship according to the present embodiment. Specifically, FIG. 51is a diagram illustrating a reference relationship in an octreestructure, and FIG. 52 is a diagram illustrating a referencerelationship in a spatial region.

In the present embodiment, when the three-dimensional data encodingdevice encodes encoding information of a current node to be encoded(hereinafter referred to as a current node), the three-dimensional dataencoding device refers to encoding information of each node in a parentnode to which the current node belongs. In this regard, however, thethree-dimensional encoding device does not refer to encoding informationof each node in another node (hereinafter referred to as a parentneighbor node) that is in the same layer as the parent node. In otherwords, the three-dimensional data encoding device disables or prohibitsreference to a parent neighbor node.

It should be noted that the three-dimensional data encoding device maypermit reference to encoding information of a parent node (hereinafteralso referred to as a grandparent node) of the parent node. In otherwords, the three-dimensional data encoding device may encode theencoding information of the current node by reference to the encodinginformation of each of the grandparent node and the parent node to whichthe current node belongs.

Here, encoding information is, for example, an occupancy code. When thethree-dimensional data encoding device encodes the occupancy code of thecurrent node, the three-dimensional data encoding device refers toinformation (hereinafter referred to as occupancy information)indicating whether a point cloud is included in each node in the parentnode to which the current node belongs. To put it in another way, whenthe three-dimensional data encoding device encodes the occupancy code ofthe current node, the three-dimensional data encoding device refers toan occupancy code of the parent node. On the other hand, thethree-dimensional data encoding device does not refer to occupancyinformation of each node in a parent neighbor node. In other words, thethree-dimensional data encoding device does not refer to an occupancycode of the parent neighbor node. Moreover, the three-dimensional dataencoding device may refer to occupancy information of each node in thegrandparent node. In other words, the three-dimensional data encodingdevice may refer to the occupancy information of each of the parent nodeand the parent neighbor node.

For example, when the three-dimensional data encoding device encodes theoccupancy code of the current node, the three-dimensional data encodingdevice selects a coding table to be used for entropy encoding of theoccupancy code of the current node, using the occupancy code of thegrandparent node or the parent node to which the current node belongs.It should be noted that the details will be described later. At thistime, the three-dimensional data encoding device need not refer to theoccupancy code of the parent neighbor node. Since this enables thethree-dimensional data encoding device to, when encoding the occupancycode of the current node, appropriately select a coding table accordingto information of the occupancy code of the parent node or thegrandparent node, the three-dimensional data encoding device can improvethe coding efficiency. Moreover, by not referring to the parent neighbornode, the three-dimensional data encoding device can suppress a processof checking the information of the parent neighbor node and reduce amemory capacity for storing the information. Furthermore, scanning theoccupancy code of each node of the octree in a depth-first order makesencoding easy.

The following describes an example of selecting a coding table using anoccupancy code of a parent node. FIG. 53 is a diagram illustrating anexample of a current node and neighboring reference nodes. FIG. 54 is adiagram illustrating a relationship between a parent node and nodes.FIG. 55 is a diagram illustrating an example of an occupancy code of theparent node. Here, a neighboring reference node is a node referred towhen a current node is encoded, among nodes spatially neighboring thecurrent node. In the example shown in FIG. 53, the neighboring nodesbelong to the same layer as the current node. Moreover, node Xneighboring the current node in the x direction, node Y neighboring thecurrent block in the y direction, and node Z neighboring the currentblock in the z direction are used as the reference neighboring nodes. Inother words, one neighboring node is set as a reference neighboring nodein each of the x, y, and z directions.

It should be noted that the node numbers shown in FIG. 54 are oneexample, and a relationship between node numbers and node positions isnot limited to the relationship shown in FIG. 54. Although node 0 isassigned to the lowest-order bit and node 7 is assigned to thehighest-order bit in FIG. 55, assignments may be made in reverse order.In addition, each node may be assigned to any bit.

The three-dimensional data encoding device determines a coding table tobe used when the three-dimensional data encoding device entropy encodesan occupancy code of a current node, using the following equation, forexample.

CodingTable=(FlagX<<2)+(FlagY<<1)+(FlagZ)

Here, CodingTable indicates a coding table for an occupancy code of acurrent node, and indicates one of values ranging from 0 to 7. FlagX isoccupancy information of neighboring node X. FlagX indicates 1 whenneighboring node X includes a point cloud (is occupied), and indicates 0when it does not. FlagY is occupancy information of neighboring node Y.FlagY indicates 1 when neighboring node Y includes a point cloud (isoccupied), and indicates 0 when it does not. FlagZ is occupancyinformation of neighboring node Z. FlagZ indicates 1 when neighboringnode Z includes a point cloud (is occupied), and indicates 0 when itdoes not.

It should be noted that since information indicating whether aneighboring node is occupied is included in an occupancy code of aparent node, the three-dimensional data encoding device may select acoding table using a value indicated by the occupancy code of the parentnode.

From the foregoing, the three-dimensional data encoding device canimprove the coding efficiency by selecting a coding table using theinformation indicating whether the neighboring node of the current nodeincludes a point cloud.

Moreover, as illustrated in FIG. 53, the three-dimensional data encodingdevice may select a neighboring reference node according to a spatialposition of the current node in the parent node. In other words, thethree-dimensional data encoding device may select a neighboring node tobe referred to from the neighboring nodes, according to the spatialposition of the current node in the parent node.

Next, the following describes examples of configurations of thethree-dimensional data encoding device and the three-dimensional datadecoding device. FIG. 56 is a block diagram of three-dimensionalencoding device 2100 according to the present embodiment.Three-dimensional data encoding device 2100 illustrated in FIG. 56includes octree generator 2101, geometry information calculator 2102,coding table selector 2103, and entropy encoder 2104.

Octree generator 2101 generates, for example, an octree from inputtedthree-dimensional points (a point cloud), and generates an occupancycode for each node included in the octree. Geometry informationcalculator 2102 obtains occupancy information indicating whether aneighboring reference node of a current node is occupied. For example,geometry information calculator 2102 obtains the occupancy informationof the neighboring reference node from an occupancy code of a parentnode to which the current node belongs. It should be noted that, asillustrated in FIG. 53, geometry information calculator 2102 may selecta neighboring reference node according to a position of the current nodein the parent node. In addition, geometry information calculator 2102does not refer to occupancy information of each node in a parentneighbor node.

Coding table selector 2103 selects a coding table to be used for entropyencoding of an occupancy code of the current node, using the occupancyinformation of the neighboring reference node calculated by geometryinformation calculator 2102. Entropy encoder 2104 generates a bitstreamby entropy encoding the occupancy code using the selected coding table.It should be noted that entropy encoder 2104 may append, to thebitstream, information indicating the selected coding table.

FIG. 57 is a block diagram of three-dimensional decoding device 2110according to the present embodiment. Three-dimensional data decodingdevice 2110 illustrated in FIG. 57 includes octree generator 2111,geometry information calculator 2112, coding table selector 2113, andentropy decoder 2114.

Octree generator 2111 generates an octree of a space (nodes) usingheader information of a bitstream etc. Octree generator 2111 generatesan octree by, for example, generating a large space (a root node) usingthe size of a space along the x-axis, y-axis, and z-axis directionsappended to the header information, and generating eight small spaces A(nodes A0 to A7) by dividing the space into two along each of thex-axis, y-axis, and z-axis directions. Nodes A0 to A7 are set as acurrent node in sequence.

Geometry information calculator 2112 obtains occupancy informationindicating whether a neighboring reference node of a current node isoccupied. For example, geometry information calculator 2112 obtains theoccupancy information of the neighboring reference node from anoccupancy code of a parent node to which the current node belongs. Itshould be noted that, as illustrated in FIG. 53, geometry informationcalculator 2112 may select a neighboring reference node according to aposition of the current node in the parent node. In addition, geometryinformation calculator 2112 does not refer to occupancy information ofeach node in a parent neighboring node.

Coding table selector 2113 selects a coding table (a decoding table) tobe used for entropy decoding of the occupancy code of the current node,using the occupancy information of the neighboring reference nodecalculated by geometry information calculator 2112. Entropy decoder 2114generates three-dimensional points by entropy decoding the occupancycode using the selected coding table. It should be noted that codingtable selector 2113 may obtain, by performing decoding, information ofthe selected coding table appended to the bitstream, and entropy decoder2114 may use a coding table indicated by the obtained information.

Each bit of the occupancy code (8 bits) included in the bitstreamindicates whether a corresponding one of eight small spaces A (nodes A0to A7) includes a point cloud. Furthermore, the three-dimensional datadecoding device generates an octree by dividing small space node A0 intoeight small spaces B (nodes B0 to B7), and obtains informationindicating whether each node of small space B includes a point cloud, bydecoding the occupancy code. In this manner, the three-dimensional datadecoding device decodes the occupancy code of each node while generatingan octree by dividing a large space into small spaces.

The following describes procedures for processes performed by thethree-dimensional data encoding device and the three-dimensional datadecoding device. FIG. 58 is a flowchart of a three-dimensional dataencoding process in the three-dimensional data encoding device. First,the three-dimensional data encoding device determines (defines) a space(a current node) including part or whole of an inputtedthree-dimensional point cloud (S2101). Next, the three-dimensional dataencoding device generates eight small spaces (nodes) by dividing thecurrent node into eight (S2102). Then, the three-dimensional dataencoding device generates an occupancy code for the current nodeaccording to whether each node includes a point cloud (S2103).

After that, the three-dimensional data encoding device calculates(obtains) occupancy information of a neighboring reference node of thecurrent node from an occupancy code of a parent node of the current node(S2104). Next, the three-dimensional data encoding device selects acoding table to be used for entropy encoding, based on the calculatedoccupancy information of the neighboring reference node of the currentnode (S2105). Then, the three-dimensional data encoding device entropyencodes the occupancy code of the current node using the selected codingtable (S2106).

Finally, the three-dimensional data encoding device repeats a process ofdividing each node into eight and encoding an occupancy code of thenode, until the node cannot be divided (S2107). In other words, stepsS2102 to S2106 are recursively repeated.

FIG. 59 is a flowchart of a three-dimensional data decoding process inthe three-dimensional data decoding device. First, the three-dimensionaldata decoding device determines (defines) a space (a current node) to bedecoded, using header information of a bitstream (S2111). Next, thethree-dimensional data decoding device generates eight small spaces(nodes) by dividing the current node into eight (S2112). Then, thethree-dimensional data decoding device calculates (obtains) occupancyinformation of a neighboring reference node of the current node from anoccupancy code of a parent node of the current node (S2113).

After that, the three-dimensional data decoding device selects a codingtable to be used for entropy decoding, based on the occupancyinformation of the neighboring reference node (S2114). Next, thethree-dimensional data decoding device entropy decodes the occupancycode of the current node using the selected coding table (S2115).

Finally, the three-dimensional data decoding device repeats a process ofdividing each node into eight and decoding an occupancy code of thenode, until the node cannot be divided (S2116). In other words, stepsS2112 to S2115 are recursively repeated.

Next, the following describes an example of selecting a coding table.FIG. 60 is a diagram illustrating an example of selecting a codingtable. For example, as in coding table 0 shown in FIG. 60, the samecontext mode may be applied to occupancy codes. Moreover, a differentcontext model may be assigned to each occupancy code. Since this enablesassignment of a context model in accordance with a probability ofappearance of an occupancy code, it is possible to improve the codingefficiency. Furthermore, a context mode that updates a probability tablein accordance with an appearance frequency of an occupancy code may beused. Alternatively, a context model having a fixed probability tablemay be used.

Hereinafter, Variation 1 of the present embodiment will be described.FIG. 61 is a diagram illustrating a reference relationship in thepresent variation. Although the three-dimensional data encoding devicedoes not refer to the occupancy code of the parent neighbor node in theabove-described embodiment, the three-dimensional data encoding devicemay switch whether to refer to an occupancy code of a parent neighbornode, according to a specific condition.

For example, when the three-dimensional data encoding device encodes anoctree while scanning the octree breadth-first, the three-dimensionaldata encoding device encodes an occupancy code of a current node byreference to occupancy information of a node in a parent neighbor node.In contrast, when the three-dimensional data encoding device encodes theoctree while scanning the octree depth-first, the three-dimensional dataencoding device prohibits reference to the occupancy information of thenode in the parent neighbor node. By appropriately selecting a referablenode according to the scan order (encoding order) of nodes of the octreein the above manner, it is possible to improve the coding efficiency andreduce the processing load.

It should be noted that the three-dimensional data encoding device mayappend, to a header of a bitstream, information indicating, for example,whether an octree is encoded breadth-first or depth-first. FIG. 62 is adiagram illustrating an example of a syntax of the header information inthis case. octree_scan_order shown in FIG. 62 is encoding orderinformation (an encoding order flag) indicating an encoding order for anoctree. For example, when octree_scan_order is 0, breadth-first isindicated, and when octree_scan_order is 1, depth-first is indicated.Since this enables the three-dimensional data decoding device todetermine whether a bitstream has been encoded breadth-first ordepth-first by reference to octree_scan_order, the three-dimensionaldata decoding device can appropriately decode the bitstream

Moreover, the three-dimensional data encoding device may append, toheader information of a bitstream, information indicating whether toprohibit reference to a parent neighbor node. FIG. 63 is a diagramillustrating an example of a syntax of the header information in thiscase. limit_refer_flag is prohibition switch information (a prohibitionswitch flag) indicating whether to prohibit reference to a parentneighbor node. For example, when limit_refer_flag is 1, prohibition ofreference to the parent neighbor node is indicated, and whenlimit_refer_flag is 0, no reference limitation (permission of referenceto the parent neighbor node) is indicated.

In other words, the three-dimensional data encoding device determineswhether to prohibit the reference to the parent neighbor node, andselects whether to prohibit or permit the reference to the parentneighbor node, based on a result of the above determination. Inaddition, the three-dimensional data encoding device generates abitstream including prohibition switch information that indicates theresult of the determination and indicates whether to prohibit thereference to the parent neighbor node.

The three-dimensional data decoding device obtains, from a bitstream,prohibition switch information indicating whether to prohibit referenceto a parent neighbor node, and selects whether to prohibit or permit thereference to the parent neighbor node, based on the prohibition switchinformation.

This enables the three-dimensional data encoding device to control thereference to the parent neighbor node and generate the bitstream. Thatalso enables the three-dimensional data decoding device to obtain, fromthe header of the bitstream, the information indicating whether toprohibit the reference to the parent neighbor node.

Although the process of encoding an occupancy code has been described asan example of an encoding process in which reference to a parentneighbor node is prohibited in the present embodiment, the presentdisclosure is not necessarily limited to this. For example, the samemethod can be applied when other information of a node of an octree isencoded. For example, the method of the present embodiment may beapplied when other attribute information, such as a color, a normalvector, or a degree of reflection, added to a node is encoded.Additionally, the same method can be applied when a coding table or apredicted value is encoded.

Hereinafter, Variation 2 of the present embodiment will be described. Inthe above description, as illustrated in FIG. 53, the example in whichthe three reference neighboring nodes are used is given, but four ormore reference neighboring nodes may be used. FIG. 64 is a diagramillustrating an example of a current node and neighboring referencenodes.

For example, the three-dimensional data encoding device calculates acoding table to be used when the three-dimensional data encoding deviceentropy encodes an occupancy code of the current node shown in FIG. 64,using the following equation.

CodingTable=(FlagX0<<3)+(FlagX1<<2)+(FlagY<<1)+(FlagZ)

Here, CodingTable indicates a coding table for an occupancy code of acurrent node, and indicates one of values ranging from 0 to 15. FlagXNis occupancy information of neighboring node XN (N=0 . . . 1). FlaxXNindicates 1 when neighboring node XN includes a point cloud (isoccupied), and indicates 0 when it does not. FlagY is occupancyinformation of neighboring node Y. FlagY indicates 1 when neighboringnode Y includes a point cloud (is occupied), and indicates 0 when itdoes not. FlagZ is occupancy information of neighboring node Z. FlagZindicates 1 when neighboring node Z includes a point cloud (isoccupied), and indicates 0 when it does not.

At this time, when a neighboring node, for example, neighboring node X0in FIG. 64, is unreferable (prohibited from being referred to), thethree-dimensional data encoding device may use, as a substitute value, afixed value such as 1 (occupied) or 0 (unoccupied).

FIG. 65 is a diagram illustrating an example of a current node andneighboring reference nodes. As illustrated in FIG. 65, when aneighboring node is unreferable (prohibited from being referred to),occupancy information of the neighboring node may be calculated byreference to an occupancy code of a grandparent node of the currentnode. For example, the three-dimensional data encoding device maycalculate FlagX0 in the above equation using occupancy information ofneighboring node G0 instead of neighboring node X0 illustrated in FIG.65, and may determine a value of a coding table using calculated FlagX0.It should be noted that neighboring node G0 illustrated in FIG. 65 is aneighboring node occupancy or unoccupancy of which can be determinedusing the occupancy code of the grandparent node. Neighboring node X1 isa neighboring node occupancy or unoccupancy of which can be determinedusing an occupancy code of a parent node.

Hereinafter, Variation 3 of the present embodiment will be described.FIG. 66 and FIG. 67 each are a diagram illustrating a referencerelationship according to the present variation. Specifically, FIG. 66is a diagram illustrating a reference relationship in an octreestructure, and FIG. 67 is a diagram illustrating a referencerelationship in a spatial region.

In the present variation, when the three-dimensional data encodingdevice encodes encoding information of a current node to be encoded(hereinafter referred to as current node 2), the three-dimensional dataencoding device refers to encoding information of each node in a parentnode to which current node 2 belongs. In other words, thethree-dimensional data encoding device permits reference to information(e.g., occupancy information) of a child node of a first node, amongneighboring nodes, that has the same parent node as a current node. Forexample, when the three-dimensional data encoding device encodes anoccupancy code of current node 2 illustrated in FIG. 66, thethree-dimensional data encoding device refers to an occupancy code of anode in the parent node to which current node 2 belongs, for example,the current node illustrated in FIG. 66. As illustrated in FIG. 67, theoccupancy code of the current node illustrated in FIG. 66 indicates, forexample, whether each node in the current node neighboring current node2 is occupied. Accordingly, since the three-dimensional data encodingdevice can select a coding table for the occupancy code of current node2 in accordance with a more particular shape of the current node, thethree-dimensional data encoding device can improve the codingefficiency.

The three-dimensional data encoding device may calculate a coding tableto be used when the three-dimensional data encoding device entropyencodes the occupancy code of current node 2, using the followingequation, for example.

CodingTable=(FlagX1<<5)+(FlagX2<<4)+(FlagX3<<3)+(FlagX4<<2)+(FlagY<<1)+(FlagZ)

Here, CodingTable indicates a coding table for an occupancy code ofcurrent node 2, and indicates one of values ranging from 0 to 63. FlagXNis occupancy information of neighboring node XN (N=1 . . . 4). FlagXNindicates 1 when neighboring node XN includes a point cloud (isoccupied), and indicates 0 when it does not. FlagY is occupancyinformation of neighboring node Y. FlagY indicates 1 when neighboringnode Y includes a point cloud (is occupied), and indicates 0 when itdoes not. FlagZ is occupancy information of neighboring node Z. FlagZindicates 1 when neighboring node Z includes a point cloud (isoccupied), and indicates 0 when it does not.

It should be noted that the three-dimensional data encoding device maychange a method of calculating a coding table, according to a nodeposition of current node 2 in the parent node.

When reference to a parent neighbor node is not prohibited, thethree-dimensional data encoding device may refer to encoding informationof each node in the parent neighbor node. For example, when thereference to the parent neighbor node is not prohibited, reference toinformation (e.g., occupancy information) of a child node of a thirdnode having a different parent node from that of a current node. In theexample illustrated in FIG. 65, for example, the three-dimensional dataencoding device obtains occupancy information of a child node ofneighboring node X0 by reference to an occupancy code of neighboringnode X0 having a different parent node from that of the current node.The three-dimensional data encoding device selects a coding table to beused for entropy encoding of an occupancy code of the current node,based on the obtained occupancy information of the child node ofneighboring node X0.

As stated above, the three-dimensional data encoding device according tothe present embodiment encodes information (e.g., an occupancy code) ofa current node included in an N-ary tree structure of three-dimensionalpoints included in three-dimensional data, where N is an integer greaterthan or equal to 2. As illustrated in FIG. 51 and FIG. 52, in theencoding, the three-dimensional data encoding device permits referenceto information (e.g., occupancy information) of a first node included inneighboring nodes spatially neighboring the current node, and prohibitsreference to information of a second node included in the neighboringnodes, the first node having a same parent node as the current node, thesecond node having a different parent node from the parent node of thecurrent node. To put it another way, in the encoding, thethree-dimensional data encoding device permits reference to information(e.g., an occupancy code) of the parent node, and prohibits reference toinformation (e.g., an occupancy code) of another node (a parent neighbornode) in the same layer as the parent node.

With this, the three-dimensional data encoding device can improve codingefficiency by reference to the information of the first node included inthe neighboring nodes spatially neighboring the current node, the firstnode having the same parent node as the current node. Besides, thethree-dimensional data encoding device can reduce a processing amount bynot reference to the information of the second node included in theneighboring nodes, the second node having a different parent node fromthe parent node of the current node. In this manner, thethree-dimensional data encoding device can not only improve the codingefficiency but also reduce the processing amount.

For example, the three-dimensional data encoding device furtherdetermines whether to prohibit the reference to the information of thesecond node. In the encoding, the three-dimensional data encoding deviceselects whether to prohibit or permit the reference to the informationof the second node, based on a result of the determining. Moreover, thethree-dimensional data encoding device generates a bit stream includingprohibition switch information (e.g., limit_refer_flag shown in FIG. 63)that indicates the result of the determining and indicates whether toprohibit the reference to the information of the second node.

With this, the three-dimensional data encoding device can select whetherto prohibit the reference to the information of the second node. Inaddition, a three-dimensional data decoding device can appropriatelyperform a decoding process using the prohibition switch information.

For example, the information of the current node is information (e.g.,an occupancy code) that indicates whether a three-dimensional point ispresent in each of child nodes belonging to the current node. Theinformation of the first node is information (the occupancy informationof the first node) that indicates whether a three-dimensional point ispresent in the first node. The information of the second node isinformation (the occupancy information of the second node) thatindicates whether a three-dimensional point is present in the secondnode.

For example, in the encoding, the three-dimensional data encoding deviceselects a coding table based on whether the three-dimensional point ispresent in the first node, and entropy encodes the information (e.g.,the occupancy code) of the current node using the coding table selected.

For example, as illustrated in FIG. 66 and FIG. 67, in the encoding, thethree-dimensional data encoding device permits reference to information(e.g., occupancy information) of a child node of the first node, thechild node being included in the neighboring nodes.

With this, since the three-dimensional data encoding device enablesreference to more detailed information of a neighboring node, thethree-dimensional data encoding device can improve the codingefficiency.

For example, as illustrated in FIG. 53, in the encoding, thethree-dimensional data encoding device selects a neighboring node to bereferred to from the neighboring nodes according to a spatial positionof the current node in the parent node.

With this, the three-dimensional data encoding device can refer to anappropriate neighboring node according to the spatial position of thecurrent node in the parent node.

For example, the three-dimensional data encoding device includes aprocessor and memory, and the processor performs the above process usingthe memory.

The three-dimensional data decoding device according to the presentembodiment decodes information (e.g., an occupancy code) of a currentnode included in an N-ary tree structure of three-dimensional pointsincluded in three-dimensional data, where N is an integer greater thanor equal to 2. As illustrated in FIG. 51 and FIG. 52, in the decoding,the three-dimensional data decoding device permits reference toinformation (e.g., occupancy information) of a first node included inneighboring nodes spatially neighboring the current node, and prohibitsreference to information of a second node included in the neighboringnodes, the first node having a same parent node as the current node, thesecond node having a different parent node from the parent node of thecurrent node. To put it another way, in the decoding, thethree-dimensional data decoding device permits reference to information(e.g., an occupancy code) of the parent node, and prohibits reference toinformation (e.g., an occupancy code) of another node (a parent neighbornode) in the same layer as the parent node.

With this, the three-dimensional data decoding device can improve codingefficiency by reference to the information of the first node included inthe neighboring nodes spatially neighboring the current node, the firstnode having the same parent node as the current node. Besides, thethree-dimensional data decoding device can reduce a processing amount bynot reference to the information of the second node included in theneighboring nodes, the second node having a different parent node fromthe parent node of the current node. In this manner, thethree-dimensional data decoding device can not only improve the codingefficiency but also reduce the processing amount.

For example, the three-dimensional data decoding device further obtains,from a bitstream, prohibition switch information (e.g., limit_refer_flagshown in FIG. 63) indicating whether to prohibit the reference to theinformation of the second node. In the decoding, the three-dimensionaldata decoding device selects whether to prohibit or permit the referenceto the information of the second node, based on the prohibition switchinformation.

With this, the three-dimensional data decoding device can appropriatelyperform a decoding process using the prohibition switch information.

For example, the information of the current node is information (e.g.,an occupancy code) that indicates whether a three-dimensional point ispresent in each of child nodes belonging to the current node. Theinformation of the first node is information (the occupancy informationof the first node) that indicates whether a three-dimensional point ispresent in the first node. The information of the second node isinformation (the occupancy information of the second node) thatindicates whether a three-dimensional point is present in the secondnode.

For example, in the decoding, the three-dimensional data encoding deviceselects a coding table based on whether the three-dimensional point ispresent in the first node, and entropy decodes the information (e.g.,the occupancy code) of the current node using the coding table selected.

For example, as illustrated in FIG. 66 and FIG. 67, in the decoding, thethree-dimensional data decoding device permits reference to information(e.g., occupancy information) of a child node of the first node, thechild node being included in the neighboring nodes.

With this, since the three-dimensional data decoding device enablesreference to more detailed information of a neighboring node, thethree-dimensional data decoding device can improve the codingefficiency.

For example, as illustrated in FIG. 53, in the decoding, thethree-dimensional data decoding device selects a neighboring node to bereferred to from the neighboring nodes according to a spatial positionof the current node in the parent node.

With this, the three-dimensional data decoding device can refer to anappropriate neighboring node according to the spatial position of thecurrent node in the parent node.

For example, the three-dimensional data decoding device includes aprocessor and memory, and the processor performs the above process usingthe memory.

Embodiment 9

Information of a three-dimensional point cloud includes geometryinformation (geometry) and attribute information (attribute). Geometryinformation includes coordinates (x-coordinate, y-coordinate,z-coordinate) with respect to a certain point. When geometry informationis encoded, a method of representing the position of each ofthree-dimensional points in octree representation and encoding theoctree information to reduce a code amount is used instead of directlyencoding the coordinates of the three-dimensional point.

On the other hand, attribute information includes informationindicating, for example, color information (RGB, YUV, etc.) of eachthree-dimensional point, a reflectance, and a normal vector. Forexample, a three-dimensional data encoding device is capable of encodingattribute information using an encoding method different from a methodused to encode geometry information.

In the present embodiment, a method of encoding attribute information isexplained. It is to be noted that, in the present embodiment, the methodis explained based on an example case using integer values as values ofattribute information. For example, when each of RGB or YUV colorcomponents is of an 8-bit accuracy, the color component is an integervalue in a range from 0 to 255. When a reflectance value is of 10-bitaccuracy, the reflectance value is an integer in a range from 0 to 1023.It is to be noted that, when the bit accuracy of attribute informationis a decimal accuracy, the three-dimensional data encoding device maymultiply the value by a scale value to round it to an integer value sothat the value of the attribute information becomes an integer value. Itis to be noted that the three-dimensional data encoding device may addthe scale value to, for example, a header of a bitstream.

As a method of encoding attribute information of a three-dimensionalpoint, it is conceivable to calculate a predicted value of the attributeinformation of the three-dimensional point and encode a difference(prediction residual) between the original value of the attributeinformation and the predicted value. For example, when the value ofattribute information at three-dimensional point p is Ap and a predictedvalue is Pp, the three-dimensional data encoding device encodesdifferential absolute value Deffp=|Ap·Pp|. In this case, whenhighly-accurate predicted value Pp can be generated, differentialabsolute value Diffp is small. Thus, for example, it is possible toreduce the code amount by entropy encoding differential absolute valueDiffp using a coding table that reduces an occurrence bit count morewhen differential absolute value Deffp is smaller.

As a method of generating a prediction value of attribute information,it is conceivable to use attribute information of a referencethree-dimensional point that is another three-dimensional point whichneighbors a current three-dimensional point to be encoded. Here, areference three-dimensional point is a three-dimensional point in arange of a predetermined distance from the current three-dimensionalpoint. For example, when there are current three-dimensional pointp=(x1, y1, z1) and three-dimensional point q=(x2, y2, z2), thethree-dimensional data encoding device calculates Euclidean distance d(p, q) between three-dimensional point p and three-dimensional point qrepresented by (Equation A1). [Math. 1]

d(p,q)=(x1−y1)²+(x2−y2)²+(x3−y3)²  (Equation A1)

The three-dimensional data encoding device determines that the positionof three-dimensional point q is closer to the position of currentthree-dimensional point p when Euclidean distance d (p, q) is smallerthan predetermined threshold value THd, and determines to use the valueof the attribute information of three-dimensional point q to generate apredicted value of the attribute information of currentthree-dimensional point p. It is to be noted that the method ofcalculating the distance may be another method, and a Mahalanobisdistance or the like may be used. In addition, the three-dimensionaldata encoding device may determine not to use, in prediction processing,any three-dimensional point outside the predetermined range of distancefrom the current three-dimensional point. For example, whenthree-dimensional point r is present, and distance d (p, r) betweencurrent three-dimensional point p and three-dimensional point r islarger than or equal to threshold value THd, the three-dimensional dataencoding device may determine not to use three-dimensional point r forprediction. It is to be noted that the three-dimensional data encodingdevice may add the information indicating threshold value THd to, forexample, a header of a bitstream.

FIG. 68 is a diagram illustrating an example of three-dimensionalpoints. In this example, distance d (p, q) between currentthree-dimensional point p and three-dimensional point q is smaller thanthreshold value THd. Thus, the three-dimensional data encoding devicedetermines that three-dimensional point q is a referencethree-dimensional point of current three-dimensional point p, anddetermines to use the value of attribute information Aq ofthree-dimensional point q to generate predicted value Pp of attributeinformation Ap of current three-dimensional point p.

In contrast, distance d (p, r) between current three-dimensional point pand three-dimensional point r is larger than or equal to threshold valueTHd. Thus, the three-dimensional data encoding device determines thatthree-dimensional point r is not any reference three-dimensional pointof current three-dimensional point p, and determines not to use thevalue of attribute information Ar of three-dimensional point r togenerate predicted value Pp of attribute information Ap of currentthree-dimensional point p.

In addition, when encoding the attribute information of the currentthree-dimensional point using a predicted value, the three-dimensionaldata encoding device uses a three-dimensional point whose attributeinformation has already been encoded and decoded, as a referencethree-dimensional point. Likewise, when decoding the attributeinformation of a current three-dimensional point to be decoded, thethree-dimensional data decoding device uses a three-dimensional pointwhose attribute information has already been decoded, as a referencethree-dimensional point. In this way, it is possible to generate thesame predicted value at the time of encoding and decoding. Thus, abitstream of the three-dimensional point generated by the encoding canbe decoded correctly at the decoding side.

Furthermore, when encoding attribute information of each ofthree-dimensional points, it is conceivable to classify thethree-dimensional point into one of a plurality of layers using geometryinformation of the three-dimensional point and then encode the attributeinformation. Here, each of the layers classified is referred to as aLevel of Detail (LoD). A method of generating LoDs is explained withreference to FIG. 69.

First, the three-dimensional data encoding device selects initial pointa0 and assigns initial point a0 to LoD0. Next, the three-dimensionaldata encoding device extracts point a1 distant from point a0 more thanthreshold value Thres_LoD[0] of LoD0 and assigns point a1 to LoD0. Next,the three-dimensional data encoding device extracts point a2 distantfrom point a1 more than threshold value Thres_LoD[0] of LoD0 and assignspoint a2 to LoD0. In this way, the three-dimensional data encodingdevice configures LoD0 in such a manner that the distance between thepoints in LoD0 is larger than threshold value Thres_LoD[0].

Next, the three-dimensional data encoding device selects point b0 whichhas not yet been assigned to any LoD and assigns point b0 to LoD1. Next,the three-dimensional data encoding device extracts point b1 which isdistant from point b0 more than threshold value Thres_LoD[1] of LoD1 andwhich has not yet been assigned to any LoD, and assigns point b1 toLoD1. Next, the three-dimensional data encoding device extracts point b2which is distant from point b1 more than threshold value Thres_LoD[1] ofLoD1 and which has not yet been assigned to any LoD, and assigns pointb2 to LoD1. In this way, the three-dimensional data encoding deviceconfigures LoD1 in such a manner that the distance between the points inLoD1 is larger than threshold value Thres_LoD[1].

Next, the three-dimensional data encoding device selects point c0 whichhas not yet been assigned to any LoD and assigns point c0 to LoD2. Next,the three-dimensional data encoding device extracts point c1 which isdistant from point c0 more than threshold value Thres_LoD[2] of LoD2 andwhich has not yet been assigned to any LoD, and assigns point c1 toLoD2. Next, the three-dimensional data encoding device extracts point c2which is distant from point c1 more than threshold value Thres_LoD[2] ofLoD2 and which has not yet been assigned to any LoD, and assigns pointc2 to LoD2. In this way, the three-dimensional data encoding deviceconfigures LoD2 in such a manner that the distance between the points inLoD2 is larger than threshold value Thres_LoD[2]. For example, asillustrated in FIG. 70, threshold values Thres_LoD[0], Thres_LoD[1], andThres_LoD[2] of respective LoDs are set.

In addition, the three-dimensional data encoding device may add theinformation indicating the threshold value of each LoD to, for example,a header of a bitstream. For example, in the case of the exampleillustrated in FIG. 70, the three-dimensional data encoding device mayadd threshold values Thres_LoD[0], Thres_LoD[1], and Thres_LoD[2] ofrespective LoDs to a header.

Alternatively, the three-dimensional data encoding device may assign allthree-dimensional points which have not yet been assigned to any LoD inthe lowermost-layer LoD. In this case, the three-dimensional dataencoding device is capable of reducing the code amount of the header bynot assigning the threshold value of the lowermost-layer LoD to theheader. For example, in the case of the example illustrated in FIG. 70,the three-dimensional data encoding device assigns threshold valuesThres_LoD[0] and Thres_LoD[1] to the header, and does not assignThres_LoD[2] to the header. In this case, the three-dimensional dataencoding device may estimate value 0 of Thres_LoD[2].

In addition, the three-dimensional data encoding device may add thenumber of LoDs to a header. In this way, the three-dimensional dataencoding device is capable of determining the lowermost-layer LoD usingthe number of LoDs. In addition, setting threshold values for therespective layers LoDs in such a manner that a larger threshold value isset to a higher layer, as illustrated in FIG. 70, makes a higher layer(layer closer to LoD0) to have a sparse point cloud (sparse) in whichthree-dimensional points are more distant and makes a lower layer tohave a dense point cloud (dense) in which three-dimensional points arecloser. It is to be noted that, in an example illustrated in FIG. 70,LoD0 is the uppermost layer.

In addition, the method of selecting an initial three-dimensional pointat the time of setting each LoD may depend on an encoding order at thetime of geometry information encoding. For example, thethree-dimensional data encoding device configures LoD0 by selecting thethree-dimensional point encoded first at the time of the geometryinformation encoding as initial point a0 of LoD0, and selecting point a1and point a2 from initial point a0 as the origin. The three-dimensionaldata encoding device then may select the three-dimensional point whosegeometry information has been encoded at the earliest time amongthree-dimensional points which do not belong to LoD0, as initial pointb0 of LoD1. In other words, the three-dimensional data encoding devicemay select the three-dimensional point whose geometry information hasbeen encoded at the earliest time among three-dimensional points whichdo not belong to layers (LoD0 to LoDn−1) above LoDn, as initial point n0of LoDn. In this way, the three-dimensional data encoding device iscapable of configuring the same LoD as in encoding by using, indecoding, the initial point selecting method similar to the one used inthe encoding, which enables appropriate decoding of a bitstream. Morespecifically, the three-dimensional data encoding device selects thethree-dimensional point whose geometry information has been decoded atthe earliest time among three-dimensional points which do not belong tolayers above LoDn, as initial point n0 of LoDn.

Hereinafter, a description is given of a method of generating thepredicted value of the attribute information of each three-dimensionalpoint using information of LoDs. For example, when encodingthree-dimensional points starting with the three-dimensional pointsincluded in LoD0, the three-dimensional data encoding device generatescurrent three-dimensional points which are included in LoD1 usingencoded and decoded (hereinafter also simply referred to as “encoded”)attribute information included in LoD0 and LoD1. In this way, thethree-dimensional data encoding device generates a predicted value ofattribute information of each three-dimensional point included in LoDnusing encoded attribute information included in LoDn′ (n′<n). In otherwords, the three-dimensional data encoding device does not use attributeinformation of each of three-dimensional points included in any layerbelow LoDn to calculate a predicted value of attribute information ofeach of the three-dimensional points included in LoDn.

For example, the three-dimensional data encoding device calculates anaverage of attribute information of N or less three dimensional pointsamong encoded three-dimensional points surrounding a currentthree-dimensional point to be encoded, to generate a predicted value ofattribute information of the current three-dimensional point. Inaddition, the three-dimensional data encoding device may add value N to,for example, a header of a bitstream. It is to be noted that thethree-dimensional data encoding device may change value N for eachthree-dimensional point, and may add value N for each three-dimensionalpoint. This enables selection of appropriate N for eachthree-dimensional point, which makes it possible to increase theaccuracy of the predicted value. Accordingly, it is possible to reducethe prediction residual. Alternatively, the three-dimensional dataencoding device may add value N to a header of a bitstream, and may fixthe value indicating N in the bitstream. This eliminates the need toencode or decode value N for each three-dimensional point, which makesit possible to reduce the processing amount. In addition, thethree-dimensional data encoding device may encode the values of Nseparately for each LoD. In this way, it is possible to increase thecoding efficiency by selecting appropriate N for each LoD.

Alternatively, the three-dimensional data encoding device may calculatea predicted value of attribute information of three-dimensional pointbased on weighted average values of attribute information of encoded Nneighbor three-dimensional points. For example, the three-dimensionaldata encoding device calculates weights using distance informationbetween a current three-dimensional point and each of N neighborthree-dimensional points.

When encoding value N for each LoD, for example, the three-dimensionaldata encoding device sets larger value N to a higher layer LoD, and setssmaller value N to a lower layer LoD. The distance betweenthree-dimensional points belonging to a higher layer LoD is large, thereis a possibility that it is possible to increase the prediction accuracyby setting large value N, selecting a plurality of neighborthree-dimensional points, and averaging the values. Furthermore, thedistance between three-dimensional points belonging to a lower layer LoDis small, it is possible to perform efficient prediction while reducingthe processing amount of averaging by setting smaller value N.

FIG. 71 is a diagram illustrating an example of attribute information tobe used for predicted values. As described above, the predicted value ofpoint P included in LoDN is generated using encoded neighbor point P′included in LoDN′ (N′≤N). Here, neighbor point P′ is selected based onthe distance from point P. For example, the predicted value of attributeinformation of point b2 illustrated in FIG. 71 is generated usingattribute information of each of points a0, a1, b0, and b1.

Neighbor points to be selected vary depending on the values of Ndescribed above. For example, in the case of N=5, a0, a1, a2, b0, and b1are selected as neighbor points. In the case of N=4, a0, a1, a2, and b1are selected based on distance information.

The predicted value is calculated by distance-dependent weightedaveraging. For example, in the example illustrated in FIG. 71, predictedvalue alp of point a2 is calculated by weighted averaging of attributeinformation of each of point a0 and a1, as represented by (Equation A2)and (Equation A3). It is to be noted that A_(i) is an attributeinformation value of ai.

$\begin{matrix}\left\lbrack {{Math}.2} \right\rbrack &  \\{{a2p} = {\sum\limits_{i = 0}^{1}{w_{i} \times A_{i}}}} & \left( {{Equation}{A2}} \right)\end{matrix}$ $\begin{matrix}{w_{i} = \frac{\frac{1}{d\left( {{a2},{ai}} \right)}}{\sum_{j = 0}^{1}\frac{1}{d\left( {{a2},{aj}} \right)}}} & \left( {{Equation}{A3}} \right)\end{matrix}$

In addition, predicted value b2p of point b2 is calculated by weightedaveraging of attribute information of each of point a0, a1, a2, b0, andb1, as represented by (Equation A4) and (Equation A6). It is to be notedthat 13, is an attribute information value of bi.

$\begin{matrix}\begin{matrix}\left\lbrack {{Math}.3} \right\rbrack &  \\{{b2p} = {{\sum_{i = 0}^{2}{{wa}_{i} \times A_{i}}} + {\sum_{i = 0}^{1}{{wb}_{i} \times B_{i}}}}} & \left( {{Equation}{A4}} \right)\end{matrix} \\\begin{matrix}{{wa}_{i} = \frac{\frac{1}{d\left( {{b2},{ai}} \right)}}{{\sum_{j = 0}^{2}\frac{1}{d\left( {{b2},{aj}} \right)}} + {\sum_{j = 0}^{1}\frac{1}{d\left( {{b2},{bj}} \right)}}}} & \left( {{Equation}{A5}} \right)\end{matrix} \\\begin{matrix}{{wb}_{i} = \frac{\frac{1}{d\left( {{b2},{bi}} \right)}}{{\sum_{j = 0}^{2}\frac{1}{d\left( {{b2},{aj}} \right)}} + {\sum_{j = 0}^{1}\frac{1}{d\left( {{b2},{bj}} \right)}}}} & \left( {{Equation}{A6}} \right)\end{matrix}\end{matrix}$

In addition, the three-dimensional data encoding device may calculate adifference value (prediction residual) generated from the value ofattribute information of a three-dimensional point and neighbor points,and may quantize the calculated prediction residual. For example, thethree-dimensional data encoding device performs quantization by dividingthe prediction residual by a quantization scale (also referred to as aquantization step). In this case, an error (quantization error) whichmay be generated by quantization reduces as the quantization scale issmaller. In the other case where the quantization scale is larger, theresulting quantization error is larger.

It is to be noted that the three-dimensional data encoding device maychange the quantization scale to be used for each LoD. For example, thethree-dimensional data encoding device reduces the quantization scalemore for a higher layer, and increases the quantization scale more for alower layer. The value of attribute information of a three-dimensionalpoint belonging to a higher layer may be used as a predicted value ofattribute information of a three-dimensional point belonging to a lowerlayer. Thus, it is possible to increase the coding efficiency byreducing the quantization scale for the higher layer to reduce thequantization error that can be generated in the higher layer and toincrease the prediction accuracy of the predicted value. It is to benoted that the three-dimensional data encoding device may add thequantization scale to be used for each LoD to, for example, a header. Inthis way, the three-dimensional data encoding device can decode thequantization scale correctly, thereby appropriately decoding thebitstream.

In addition, the three-dimensional data encoding device may convert asigned integer value (signed quantized value) which is a quantizedprediction residual into an unsigned integer value (unsigned quantizedvalue). This eliminates the need to consider occurrence of a negativeinteger when entropy encoding the prediction residual. It is to be notedthat the three-dimensional data encoding device does not always need toconvert a signed integer value into an unsigned integer value, and, forexample, that the three-dimensional data encoding device may entropyencode a sign bit separately.

The prediction residual is calculated by subtracting a prediction valuefrom the original value. For example, as represented by (Equation A7),prediction residual a2r of point a2 is calculated by subtractingpredicted value a2p of point a2 from value A₂ of attribute informationof point a2. As represented by (Equation A8), prediction residual b2r ofpoint b2 is calculated by subtracting predicted value b2p of point b2from value B2 of attribute information of point b2.

a2 r=A ₂ ·a2 p  (Equation A7)

b2 r=B ₂ ·b2 p  (Equation A8)

In addition, the prediction residual is quantized by being divided by aQuantization Step (QS). For example, quantized value a2q of point a2 iscalculated according to (Equation A9). Quantized value b2q of point b2is calculated according to (Equation A10). Here, QS_LoD0 is a QS forLoD0, and QS_LoD1 is a QS for LoD1. In other words, a QS may be changedaccording to an LoD.

a 2 q=a 2 r/QS_LoD 0  (Equation A9)

b 2 q=b 2 r/QS_LoD 1  (Equation A10)

In addition, the three-dimensional data encoding device converts signedinteger values which are quantized values as indicated below intounsigned integer values as indicated below. When signed integer valuea2q is smaller than 0, the three-dimensional data encoding device setsunsigned integer value a2u to −1−(2×a2q). When signed integer value a2qis 0 or more, the three-dimensional data encoding device sets unsignedinteger value a2u to 2×a2q.

Likewise, when signed integer value b2q is smaller than 0, thethree-dimensional data encoding device sets unsigned integer value b2uto −1−(2×b2q). When signed integer value b2q is 0 or more, thethree-dimensional data encoding device sets unsigned integer value b2uto 2×b2q.

In addition, the three-dimensional data encoding device may encode thequantized prediction residual (unsigned integer value) by entropyencoding. For example, the three-dimensional data encoding device maybinarize the unsigned integer value and then apply binary arithmeticencoding to the binary value.

It is to be noted that, in this case, the three-dimensional dataencoding device may switch binarization methods according to the valueof a prediction residual. For example, when prediction residual pu issmaller than threshold value R_TH, the three-dimensional data encodingdevice binarizes prediction residual pu using a fixed bit count requiredfor representing threshold value R_TH. In addition, when predictionresidual pu is larger than or equal to threshold value R_TH, thethree-dimensional data encoding device binarizes the binary data ofthreshold value R_TH and the value of (pu·R_TH), usingexponential-Golomb coding, or the like.

For example, when threshold value R_TH is 63 and prediction residual puis smaller than 63, the three-dimensional data encoding device binarizesprediction residual pu using 6 bits. When prediction residual pu islarger than or equal to 63, the three-dimensional data encoding deviceperforms arithmetic encoding by binarizing the binary data (111111) ofthreshold value R_TH and (pu·63) using exponential-Golomb coding.

In a more specific example, when prediction residual pu is 32, thethree-dimensional data encoding device generates 6-bit binary data(100000), and arithmetic encodes the bit sequence. In addition, whenprediction residual pu is 66, the three-dimensional data encoding devicegenerates binary data (111111) of threshold value R_TH and a bitsequence (00100) representing value 3 (66-63) using exponential-Golombcoding, and arithmetic encodes the bit sequence (111111+00100).

In this way, the three-dimensional data encoding device can performencoding while preventing a binary bit count from increasing abruptly inthe case where a prediction residual becomes large by switchingbinarization methods according to the magnitude of the predictionresidual. It is to be noted that the three-dimensional data encodingdevice may add threshold value R_TH to, for example, a header of abitstream.

For example, in the case where encoding is performed at a high bit rate,that is, when a quantization scale is small, a small quantization errorand a high prediction accuracy are obtained. As a result, a predictionresidual may not be large. Thus, in this case, the three-dimensionaldata encoding device sets large threshold value R_TH. This reduces thepossibility that the binary data of threshold value R_TH is encoded,which increases the coding efficiency. In the opposite case whereencoding is performed at a low bit rate, that is, when a quantizationscale is large, a large quantization error and a low prediction accuracyare obtained. As a result, a prediction residual may be large. Thus, inthis case, the three-dimensional data encoding device sets smallthreshold value R_TH. In this way, it is possible to prevent abruptincrease in bit length of binary data.

In addition, the three-dimensional data encoding device may switchthreshold value R_TH for each LoD, and may add threshold value R_TH foreach LoD to, for example, a header. In other words, thethree-dimensional data encoding device may switch binarization methodsfor each LoD. For example, since distances between three-dimensionalpoints are large in a higher layer, a prediction accuracy is low, whichmay increase a prediction residual. Thus, the three-dimensional dataencoding device prevents abrupt increase in bit length of binary data bysetting small threshold value R_TH to the higher layer. In addition,since distances between three-dimensional points are small in a lowerlayer, a prediction accuracy is high, which may reduce a predictionresidual. Thus, the three-dimensional data encoding device increases thecoding efficiency by setting large threshold value R_TH to the lowerlayer.

FIG. 72 is a diagram indicating examples of exponential-Golomb codes.The diagram indicates the relationships between pre-binarization values(non-binary values) and post-binarization bits (codes). It is to benoted that 0 and 1 indicated in FIG. 72 may be inverted.

The three-dimensional data encoding device applies arithmetic encodingto the binary data of prediction residuals. In this way, the codingefficiency can be increased. It is to be noted that, in the applicationof the arithmetic encoding, there is a possibility that occurrenceprobability tendencies of 0 and 1 in each bit vary, in binary data,between an n-bit code which is a part binarized by n bits and aremaining code which is a part binarized using exponential-Golombcoding. Thus, the three-dimensional data encoding device may switchmethods of applying arithmetic encoding between the n-bit code and theremaining code.

For example, the three-dimensional data encoding device performsarithmetic encoding on the n-bit code using one or more coding tables(probability tables) different for each bit. At this time, thethree-dimensional data encoding device may change the number of codingtables to be used for each bit. For example, the three-dimensional dataencoding device performs arithmetic encoding using one coding table forfirst bit b0 in an n-bit code. The three-dimensional data encodingdevice uses two coding tables for next bit b1. The three-dimensionaldata encoding device switches coding tables to be used for arithmeticencoding of bit b1 according to the value (0 or 1) of b0. Likewise, thethree-dimensional data encoding device uses four coding tables for nextbit b2. The three-dimensional data encoding device switches codingtables to be used for arithmetic encoding of bit b2 according to thevalues (in a range from 0 to 3) of b0 and b1.

In this way, the three-dimensional data encoding device uses 2^(n−1)coding tables when arithmetic encoding each bit bn−1 in n-bit code. Thethree-dimensional data encoding device switches coding tables to be usedaccording to the values (occurrence patterns) of bits before bn−1. Inthis way, the three-dimensional data encoding device can use codingtables appropriate for each bit, and thus can increase the codingefficiency.

It is to be noted that the three-dimensional data encoding device mayreduce the number of coding tables to be used for each bit. For example,the three-dimensional data encoding device may switch 2^(m) codingtables according to the values (occurrence patterns) of m bits (m<n−1)before bn−1 when arithmetic encoding each bit bn−1. In this way, it ispossible to increase the coding efficiency while reducing the number ofcoding tables to be used for each bit. It is to be noted that thethree-dimensional data encoding device may update the occurrenceprobabilities of 0 and 1 in each coding table according to the values ofbinary data occurred actually. In addition, the three-dimensional dataencoding device may fix the occurrence probabilities of 0 and 1 incoding tables for some bit(s). In this way, it is possible to reduce thenumber of updates of occurrence probabilities, and thus to reduce theprocessing amount.

For example, when an n-bit code is b0, b1, b2, . . . , bn−1, the codingtable for b0 is one table (CTb0). Coding tables for b 1 are two tables(CTb10 and CTb11). Coding tables to be used are switched according tothe value (0 or 1) of b0. Coding tables for b2 are four tables (CTb20,CTb21, CTb22, and CTb23). Coding tables to be used are switchedaccording to the values (in the range from 0 to 3) of b0 and b1. Codingtables for bn−1 are 2^(n−1) tables (CTbn0, CTbn1, . . . , CTbn(2^(n−1)-1)). Coding tables to be used are switched according to thevalues (in a range from 0 to 2^(n−1)-1) of b0, b1, . . . , bn−2.

It is to be noted that the three-dimensional data encoding device mayapply, to an n-bit code, arithmetic encoding (m=2n) by m-ary that setsthe value in the range from 0 to 2^(n)-1 without binarization. When thethree-dimensional data encoding device arithmetic encodes an n-bit codeby an m-ary, the three-dimensional data decoding device may reconstructthe n-bit code by arithmetic decoding the m-ary.

FIG. 73 is a diagram for illustrating processing in the case whereremaining codes are exponential-Golomb codes. As indicated in FIG. 73,each remaining code which is a part binarized using exponential-Golombcoding includes a prefix and a suffix. For example, thethree-dimensional data encoding device switches coding tables betweenthe prefix and the suffix. In other words, the three-dimensional dataencoding device arithmetic encodes each of bits included in the prefixusing coding tables for the prefix, and arithmetic encodes each of bitsincluded in the suffix using coding tables for the suffix.

It is to be noted that the three-dimensional data encoding device mayupdate the occurrence probabilities of 0 and 1 in each coding tableaccording to the values of binary data occurred actually. In addition,the three-dimensional data encoding device may fix the occurrenceprobabilities of 0 and 1 in one of coding tables. In this way, it ispossible to reduce the number of updates of occurrence probabilities,and thus to reduce the processing amount. For example, thethree-dimensional data encoding device may update the occurrenceprobabilities for the prefix, and may fix the occurrence probabilitiesfor the suffix.

In addition, the three-dimensional data encoding device decodes aquantized prediction residual by inverse quantization andreconstruction, and uses a decoded value which is the decoded predictionresidual for prediction of a current three-dimensional point to beencoded and the following three-dimensional point(s). More specifically,the three-dimensional data encoding device calculates an inversequantized value by multiplying the quantized prediction residual(quantized value) with a quantization scale, and adds the inversequantized value and a prediction value to obtain the decoded value(reconstructed value).

For example, quantized value a2iq of point a2 is calculated usingquantized value a2q of point a2 according to (Equation A11). Inversequantized value b2iq of point b2q is calculated using quantized valueb2q of point b2 according to (Equation A12). Here, QS_LoD0 is a QS forLoD0, and QS_LoD1 is a QS for LoD1. In other words, a QS may be changedaccording to an LoD.

a2 iq=a2 q×QS_LoD0  (Equation A11)

b2 iq=b2 q×QS_LoD1  (Equation A12)

For example, as represented by (Equation A13), decoded value a2rec ofpoint a2 is calculated by adding inverse quantization value a2iq ofpoint a2 to predicted value a2p of point a2. As represented by (EquationA14), decoded value b2rec of point b2 is calculated by adding inversequantized value b2iq of point b2 to predicted value b2p of point b2.

a2 rec=a2 iq+a2 p  (EquationA13)

b2 rec=b2 iq+b2 p  (Equation A14)

Hereinafter, a syntax example of a bitstream according to the presentembodiment is described. FIG. 74 is a diagram indicating the syntaxexample of an attribute header (attribute_header) according to thepresent embodiment. The attribute header is header information ofattribute information. As indicated in FIG. 74, the attribute headerincludes the number of layers information (NumLoD), the number ofthree-dimensional points information (NumOfPoint[i]), a layer thresholdvalue (Thres_LoD[i]), the number of neighbor points information(NumNeighborPoint[i]), a prediction threshold value (THd[i]), aquantization scale (QS[i]), and a binarization threshold value(R_TH[i]).

The number of layers information (NumLoD) indicates the number of LoDsto be used.

The number of three-dimensional points information (NumOfPoint[i])indicates the number of three-dimensional points belonging to layer i.It is to be noted that the three-dimensional data encoding device mayadd, to another header, the number of three-dimensional pointsinformation indicating the total number of three-dimensional points. Inthis case, the three-dimensional data encoding device does not need toadd, to a header, NumOfPoint [NumLoD—1] indicating the number ofthree-dimensional points belonging to the lowermost layer. In this case,the three-dimensional data decoding device is capable of calculatingNumOfPoint [NumLoD−1] according to (Equation A15). In this case, it ispossible to reduce the code amount of the header.

[Math.4] $\begin{matrix}{{{NumOfPoint}\left\lbrack {{NumLoD} - 1} \right\rbrack} = {{AllNumOfPoint} - {\sum\limits_{j = 0}^{{NumLoD} - 2}{{NumOfPoint}\lbrack j\rbrack}}}} & \left( {{Equation}{A15}} \right)\end{matrix}$

The layer threshold value (Thres_LoD[i]) is a threshold value to be usedto set layer i. The three-dimensional data encoding device and thethree-dimensional data decoding device configure LoDi in such a mannerthat the distance between points in LoDi becomes larger than thresholdvalue Thres_LoD[i]. The three-dimensional data encoding device does notneed to add the value of Thres_LoD [NumLoD−1] (lowermost layer) to aheader. In this case, the three-dimensional data decoding device mayestimate 0 as the value of Thres_LoD [NumLoD−1]. In this case, it ispossible to reduce the code amount of the header.

The number of neighbor points information (NumNeighborPoint[i])indicates the upper limit value of the number of neighbor points to beused to generate a predicted value of a three-dimensional pointbelonging to layer i. The three-dimensional data encoding device maycalculate a predicted value using the number of neighbor points M whenthe number of neighbor points M is smaller than NumNeighborPoint[i](M<NumNeighborPoint [i]). Furthermore, when there is no need todifferentiate the values of NumNeighborPoint[i] for respective LoDs, thethree-dimensional data encoding device may add a piece of the number ofneighbor points information (NumNeighborPoint) to be used in all LoDs toa header.

The prediction threshold value (THd[i]) indicates the upper limit valueof the distance between a current three-dimensional point to be encodedor decoded in layer i and each of neighbor three-dimensional points tobe used to predict the current three-dimensional point. Thethree-dimensional data encoding device and the three-dimensional datadecoding device do not use, for prediction, any three-dimensional pointdistant from the current three-dimensional point over THd[i]. It is tobe noted that, when there is no need to differentiate the values ofTHd[i] for respective LoDs, the three-dimensional data encoding devicemay add a single prediction threshold value (THd) to be used in all LoDsto a header.

The quantization scale (QS[i]) indicates a quantization scale to be usedfor quantization and inverse quantization in layer i.

The binarization threshold value (R_TH[i]) is a threshold value forswitching binarization methods of prediction residuals ofthree-dimensional points belonging to layer i. For example, thethree-dimensional data encoding device binarizes prediction residual puusing a fixed bit count when a prediction residual is smaller thanthreshold value R_TH, and binarizes the binary data of threshold valueR_TH and the value of (pu·R_TH) using exponential-Golomb coding when aprediction residual is larger than or equal to threshold value R_TH. Itis to be noted that, when there is no need to switch the values ofR_TH[i] between LoDs, the three-dimensional data encoding device may adda single binarization threshold value (R_TH) to be used in all LoDs to aheader.

It is to be noted that R_TH[i] may be the maximum value which can berepresented by n bits. For example, R_TH is 63 in the case of 6 bits,and R_TH is 255 in the case of 8 bits. Alternatively, thethree-dimensional data encoding device may encode a bit count instead ofencoding the maximum value which can be represented by n bits as abinarization threshold value. For example, the three-dimensional dataencoding device may add value 6 in the case of R_TH[i]=63 to a header,and may add value 8 in the case of R_TH[i]=255 to a header.Alternatively, the three-dimensional data encoding device may define theminimum value (minimum bit count) representing R_TH[i], and add arelative bit count from the minimum value to a header. For example, thethree-dimensional data encoding device may add value 0 to a header whenR_TH[i]=63 is satisfied and the minimum bit count is 6, and may addvalue 2 to a header when R_TH[i]=255 is satisfied and the minimum bitcount is 6.

Alternatively, the three-dimensional data encoding device may entropyencode at least one of NumLoD, Thres_LoD[i], NumNeighborPoint[i],THd[i], QS[i], and R_TH[i], and add the entropy encoded one to a header.For example, the three-dimensional data encoding device may binarizeeach value and perform arithmetic encoding on the binary value. Inaddition, the three-dimensional data encoding device may encode eachvalue using a fixed length in order to reduce the processing amount.

Alternatively, the three-dimensional data encoding device does notalways need to add at least one of NumLoD, Thres_LoD[i],NumNeighborPoint[i], THd[i], QS[i], and R_TH[i] to a header. Forexample, at least one of these values may be defined by a profile or alevel in a standard, or the like. In this way, it is possible to reducethe bit amount of the header.

FIG. 75 is a diagram indicating the syntax example of attribute data(attribute_data) according to the present embodiment. The attribute dataincludes encoded data of the attribute information of a plurality ofthree-dimensional points. As indicated in FIG. 75, the attribute dataincludes an n-bit code and a remaining code.

The n-bit code is encoded data of a prediction residual of a value ofattribute information or a part of the encoded data. The bit length ofthe n-bit code depends on value R_TH[i]. For example, the bit length ofthe n-bit code is 6 bits when the value indicated by R_TH[i] is 63, thebit length of the n-bit code is 8 bits when the value indicated byR_TH[i] is 255.

The remaining code is encoded data encoded using exponential-Golombcoding among encoded data of the prediction residual of the value of theattribute information. The remaining code is encoded or decoded when thevalue of the n-bit code is equal to R_TH[i]. The three-dimensional datadecoding device decodes the prediction residual by adding the value ofthe n-bit code and the value of the remaining code. It is to be notedthat the remaining code does not always need to be encoded or decodedwhen the value of the n-bit code is not equal to R_TH[i].

Hereinafter, a description is given of a flow of processing in thethree-dimensional data encoding device. FIG. 76 is a flowchart of athree-dimensional data encoding process performed by thethree-dimensional data encoding device.

First, the three-dimensional data encoding device encodes geometryinformation (geometry) (S3001). For example, the three-dimensional dataencoding is performed using octree representation.

When the positions of three-dimensional points changed by quantization,etc, after the encoding of the geometry information, thethree-dimensional data encoding device re-assigns attribute informationof the original three-dimensional points to the post-changethree-dimensional points (S3002). For example, the three-dimensionaldata encoding device interpolates values of attribute informationaccording to the amounts of change in position to re-assign theattribute information. For example, the three-dimensional data encodingdevice detects pre-change N three-dimensional points closer to thepost-change three-dimensional positions, and performs weighted averagingof the values of attribute information of the N three-dimensionalpoints. For example, the three-dimensional data encoding devicedetermines weights based on distances from the post-changethree-dimensional positions to the respective N three-dimensionalpositions in weighted averaging. The three-dimensional data encodingdevice then determines the values obtained through the weightedaveraging to be the values of the attribute information of thepost-change three-dimensional points. When two or more of thethree-dimensional points are changed to the same three-dimensionalposition through quantization, etc., the three-dimensional data encodingdevice may assign the average value of the attribute information of thepre-change two or more three-dimensional points as the values of theattribute information of the post-change three-dimensional points.

Next, the three-dimensional data encoding device encodes the attributeinformation (attribute) re-assigned (S3003). For example, when encodinga plurality of kinds of attribute information, the three-dimensionaldata encoding device may encode the plurality of kinds of attributeinformation in order. For example, when encoding colors and reflectancesas attribute information, the three-dimensional data encoding device maygenerate a bitstream added with the color encoding results and thereflectance encoding results after the color encoding results. It is tobe noted that the order of the plurality of encoding results ofattribute information to be added to a bitstream is not limited to theorder, and may be any order.

Alternatively, the three-dimensional data encoding device may add, to aheader for example, information indicating the start location of encodeddata of each attribute information in a bitstream. In this way, thethree-dimensional data decoding device is capable of selectivelydecoding attribute information required to be decoded, and thus iscapable of skipping the decoding process of the attribute informationnot required to be decoded. Accordingly, it is possible to reduce theamount of processing by the three-dimensional data decoding device.Alternatively, the three-dimensional data encoding device may encode aplurality of kinds of attribute information in parallel, and mayintegrate the encoding results into a single bitstream. In this way, thethree-dimensional data encoding device is capable of encoding theplurality of kinds of attribute information at high speed.

FIG. 77 is a flowchart of an attribute information encoding process(S3003). First, the three-dimensional data encoding device sets LoDs(S3011). In other words, the three-dimensional data encoding deviceassigns each of three-dimensional points to any one of the plurality ofLoDs.

Next, the three-dimensional data encoding device starts a loop for eachLoD (S3012). In other words, the three-dimensional data encoding deviceiteratively performs the processes of Steps from S3013 to S3021 for eachLoD.

Next, the three-dimensional data encoding device starts a loop for eachthree-dimensional point (S3013). In other words, the three-dimensionaldata encoding device iteratively performs the processes of Steps fromS3014 to S3020 for each three-dimensional point.

First, the three-dimensional data encoding device searches a pluralityof neighbor points which are three-dimensional points present in theneighborhood of a current three-dimensional point to be processed andare to be used to calculate a predicted value of the currentthree-dimensional point (S3014). Next, the three-dimensional dataencoding device calculates the weighted average of the values ofattribute information of the plurality of neighbor points, and sets theresulting value to predicted value P (S3015). Next, thethree-dimensional data encoding device calculates a prediction residualwhich is the difference between the attribute information of the currentthree-dimensional point and the predicted value (S3016). Next, thethree-dimensional data encoding device quantizes the prediction residualto calculate a quantized value (S3017). Next, the three-dimensional dataencoding device arithmetic encodes the quantized value (S3018).

Next, the three-dimensional data encoding device inverse quantizes thequantized value to calculate an inverse quantized value (S3019). Next,the three-dimensional data encoding device adds a prediction value tothe inverse quantized value to generate a decoded value (S3020). Next,the three-dimensional data encoding device ends the loop for eachthree-dimensional point (S3021). Next, the three-dimensional dataencoding device ends the loop for each LoD (S3022).

Hereinafter, a description is given of a three-dimensional data decodingprocess in the three-dimensional data decoding device which decodes abitstream generated by the three-dimensional data encoding device.

The three-dimensional data decoding device generates decoded binary databy arithmetic decoding the binary data of the attribute information inthe bitstream generated by the three-dimensional data encoding device,according to the method similar to the one performed by thethree-dimensional data encoding device. It is to be noted that whenmethods of applying arithmetic encoding are switched between the part(n-bit code) binarized using n bits and the part (remaining code)binarized using exponential-Golomb coding in the three-dimensional dataencoding device, the three-dimensional data decoding device performsdecoding in conformity with the arithmetic encoding, when applyingarithmetic decoding.

For example, the three-dimensional data decoding device performsarithmetic decoding using coding tables (decoding tables) different foreach bit in the arithmetic decoding of the n-bit code. At this time, thethree-dimensional data decoding device may change the number of codingtables to be used for each bit. For example, the three-dimensional datadecoding device performs arithmetic decoding using one coding table forfirst bit b0 in the n-bit code. The three-dimensional data decodingdevice uses two coding tables for next bit b1. The three-dimensionaldata decoding device switches coding tables to be used for arithmeticdecoding of bit b1 according to the value (0 or 1) of b0. Likewise, thethree-dimensional data decoding device uses four coding tables for nextbit b2. The three-dimensional data decoding device switches codingtables to be used for arithmetic decoding of bit b2 according to thevalues (in the range from 0 to 3) of b0 and b1.

In this way, the three-dimensional data decoding device uses 2^(n−1)coding tables when arithmetic decoding each bit bn−1 in the n-bit code.The three-dimensional data decoding device switches coding tables to beused according to the values (occurrence patterns) of bits before bn−1.In this way, the three-dimensional data decoding device is capable ofappropriately decoding a bitstream encoded at an increased codingefficiency using the coding tables appropriate for each bit.

It is to be noted that the three-dimensional data decoding device mayreduce the number of coding tables to be used for each bit. For example,the three-dimensional data decoding device may switch 2^(m) codingtables according to the values (occurrence patterns) of m bits (m<n−1)before bn−1 when arithmetic decoding each bit bn−1. In this way, thethree-dimensional data decoding device is capable of appropriatelydecoding the bitstream encoded at the increased coding efficiency whilereducing the number of coding tables to be used for each bit. It is tobe noted that the three-dimensional data decoding device may update theoccurrence probabilities of 0 and 1 in each coding table according tothe values of binary data occurred actually. In addition, thethree-dimensional data decoding device may fix the occurrenceprobabilities of 0 and 1 in coding tables for some bit(s). In this way,it is possible to reduce the number of updates of occurrenceprobabilities, and thus to reduce the processing amount.

For example, when an n-bit code is b0, b1, b2, . . . , bn−1, the codingtable for b0 is one (CTb0). Coding tables for b1 are two tables (CTb10and CTb11). Coding tables to be used are switched according to the value(0 or 1) of b0. Coding tables for b2 are four tables (CTb20, CTb21,CTb22, and CTb23). Coding tables to be used according to the values (inthe range from 0 to 3) of b0 and b1. Coding tables for bn−1 are 2^(n−1)tables (CTbn0, CTbn1, . . . , CTbn (2^(n−1)-1)). Coding tables to beused are switched according to the values (in the range from 0 to2^(n−1)-1) of b0, b1, . . . , bn−2.

FIG. 78 is a diagram for illustrating processing in the case whereremaining codes are exponential-Golomb codes. As indicated in FIG. 78,the part (remaining part) binarized and encoded by the three-dimensionaldata encoding device using exponential-Golomb coding includes a prefixand a suffix. For example, the three-dimensional data decoding deviceswitches coding tables between the prefix and the suffix. In otherwords, the three-dimensional data decoding device arithmetic decodeseach of bits included in the prefix using coding tables for the prefix,and arithmetic decodes each of bits included in the suffix using codingtables for the suffix.

It is to be noted that the three-dimensional data decoding device mayupdate the occurrence probabilities of 0 and 1 in each coding tableaccording to the values of binary data occurred at the time of decoding.In addition, the three-dimensional data decoding device may fix theoccurrence probabilities of 0 and 1 in one of coding tables. In thisway, it is possible to reduce the number of updates of occurrenceprobabilities, and thus to reduce the processing amount. For example,the three-dimensional data decoding device may update the occurrenceprobabilities for the prefix, and may fix the occurrence probabilitiesfor the suffix.

Furthermore, the three-dimensional data decoding device decodes thequantized prediction residual (unsigned integer value) by debinarizingthe binary data of the prediction residual arithmetic decoded accordingto a method in conformity with the encoding method used by thethree-dimensional data encoding device. The three-dimensional datadecoding device first arithmetic decodes the binary data of an n-bitcode to calculate a value of the n-bit code. Next, the three-dimensionaldata decoding device compares the value of the n-bit code with thresholdvalue R_TH.

In the case where the value of the n-bit code and threshold value R_THmatch, the three-dimensional data decoding device determines that a bitencoded using exponential-Golomb coding is present next, and arithmeticdecodes the remaining code which is the binary data encoded usingexponential-Golomb coding. The three-dimensional data decoding devicethen calculates, from the decoded remaining code, a value of theremaining code using a reverse lookup table indicating the relationshipbetween the remaining code and the value. FIG. 79 is a diagramindicating an example of a reverse lookup table indicating relationshipsbetween remaining codes and the values thereof. Next, thethree-dimensional data decoding device adds the obtained value of theremaining code to R_TH, thereby obtaining a debinarized quantizedprediction residual.

In the opposite case where the value of the n-bit code and thresholdvalue R_TH do not match (the value of the n-bit code is smaller thanvalue R_TH), the three-dimensional data decoding device determines thevalue of the n-bit code to be the debinarized quantized predictionresidual as it is. In this way, the three-dimensional data decodingdevice is capable of appropriately decoding the bitstream generatedwhile switching the binarization methods according to the values of theprediction residuals by the three-dimensional data encoding device.

It is to be noted that, when threshold value R_TH is added to, forexample, a header of a bitstream, the three-dimensional data decodingdevice may decode threshold value R_TH from the header, and may switchdecoding methods using decoded threshold value R_TH. When thresholdvalue R_TH is added to, for example, a header for each LoD, thethree-dimensional data decoding device switch decoding methods usingthreshold value R_TH decoded for each LoD.

For example, when threshold value R_TH is 63 and the value of thedecoded n-bit code is 63, the three-dimensional data decoding devicedecodes the remaining code using exponential-Golomb coding, therebyobtaining the value of the remaining code. For example, in the exampleindicated in FIG. 79, the remaining code is 00100, and 3 is obtained asthe value of the remaining code. Next, the three-dimensional datadecoding device adds 63 that is threshold value R_TH and 3 that is thevalue of the remaining code, thereby obtaining 66 that is the value ofthe prediction residual.

In addition, when the value of the decoded n-bit code is 32, thethree-dimensional data decoding device sets 32 that is the value of then-bit code to the value of the prediction residual.

In addition, the three-dimensional data decoding device converts thedecoded quantized prediction residual, for example, from an unsignedinteger value to a signed integer value, through processing inverse tothe processing in the three-dimensional data encoding device. In thisway, when entropy decoding the prediction residual, thethree-dimensional data decoding device is capable of appropriatelydecoding the bitstream generated without considering occurrence of anegative integer. It is to be noted that the three-dimensional datadecoding device does not always need to convert an unsigned integervalue to a signed integer value, and that, for example, thethree-dimensional data decoding device may decode a sign bit whendecoding a bitstream generated by separately entropy encoding the signbit.

The three-dimensional data decoding device performs decoding by inversequantizing and reconstructing the quantized prediction residual afterbeing converted to the signed integer value, to obtain a decoded value.The three-dimensional data decoding device uses the generated decodedvalue for prediction of a current three-dimensional point to be decodedand the following three-dimensional point(s). More specifically, thethree-dimensional data decoding device multiplies the quantizedprediction residual by a decoded quantization scale to calculate aninverse quantized value and adds the inverse quantized value and thepredicted value to obtain the decoded value.

The decoded unsigned integer value (unsigned quantized value) isconverted into a signed integer value through the processing indicatedbelow. When the least significant bit (LSB) of decoded unsigned integervalue a2u is 1, the three-dimensional data decoding device sets signedinteger value a2q to−((a2u+1)>>1). When the LSB of unsigned integervalue a2u is not 1, the three-dimensional data decoding device setssigned integer value a2q to ((a2u»1).

Likewise, when an LSB of decoded unsigned integer value b2u is 1, thethree-dimensional data decoding device sets signed integer value b2q to−((b2u+1)>>1). When the LSB of decoded unsigned integer value n2u is not1, the three-dimensional data decoding device sets signed integer valueb2q to ((b2u»1).

Details of the inverse quantization and reconstruction processing by thethree-dimensional data decoding device are similar to the inversequantization and reconstruction processing in the three-dimensional dataencoding device.

Hereinafter, a description is given of a flow of processing in thethree-dimensional data decoding device. FIG. 80 is a flowchart of athree-dimensional data decoding process performed by thethree-dimensional data decoding device. First, the three-dimensionaldata decoding device decodes geometry information (geometry) from abitstream (S3031). For example, the three-dimensional data decodingdevice performs decoding using octree representation.

Next, the three-dimensional data decoding device decodes attributeinformation (attribute) from the bitstream (S3032). For example, whendecoding a plurality of kinds of attribute information, thethree-dimensional data decoding device may decode the plurality of kindsof attribute information in order. For example, when decoding colors andreflectances as attribute information, the three-dimensional datadecoding device decodes the color encoding results and the reflectanceencoding results in order of assignment in the bitstream. For example,when the reflectance encoding results are added after the color encodingresults in a bitstream, the three-dimensional data decoding devicedecodes the color encoding results, and then decodes the reflectanceencoding results. It is to be noted that the three-dimensional datadecoding device may decode, in any order, the encoding results of theattribute information added to the bitstream.

Alternatively, the three-dimensional data encoding device may add, to aheader for example, information indicating the start location of encodeddata of each attribute information in a bitstream. In this way, thethree-dimensional data decoding device is capable of selectivelydecoding attribute information required to be decoded, and thus iscapable of skipping the decoding process of the attribute informationnot required to be decoded. Accordingly, it is possible to reduce theamount of processing by the three-dimensional data decoding device. Inaddition, the three-dimensional data decoding device may decode aplurality of kinds of attribute information in parallel, and mayintegrate the decoding results into a single three-dimensional pointcloud. In this way, the three-dimensional data decoding device iscapable of decoding the plurality of kinds of attribute information athigh speed.

FIG. 81 is a flowchart of an attribute information decoding process(S3032). First, the three-dimensional data decoding device sets LoDs(S3041). In other words, the three-dimensional data decoding deviceassigns each of three-dimensional points having the decoded geometryinformation to any one of the plurality of LoDs. For example, thisassignment method is the same as the assignment method used in thethree-dimensional data encoding device.

Next, the three-dimensional data decoding device starts a loop for eachLoD (S3042). In other words, the three-dimensional data decoding deviceiteratively performs the processes of Steps from S3043 to S3049 for eachLoD.

Next, the three-dimensional data decoding device starts a loop for eachthree-dimensional point (S3043). In other words, the three-dimensionaldata decoding device iteratively performs the processes of Steps fromS3044 to S3048 for each three-dimensional point.

First, the three-dimensional data decoding device searches a pluralityof neighbor points which are three-dimensional points present in theneighborhood of a current three-dimensional point to be processed andare to be used to calculate a predicted value of the currentthree-dimensional point to be processed (S3044). Next, thethree-dimensional data decoding device calculates the weighted averageof the values of attribute information of the plurality of neighborpoints, and sets the resulting value to predicted value P (S3045). It isto be noted that these processes are similar to the processes in thethree-dimensional data encoding device.

Next, the three-dimensional data decoding device arithmetic decodes thequantized value from the bitstream (S3046). The three-dimensional datadecoding device inverse quantizes the decoded quantized value tocalculate an inverse quantized value (S3047). Next, thethree-dimensional data decoding device adds a predicted value to theinverse quantized value to generate a decoded value (S3048). Next, thethree-dimensional data decoding device ends the loop for eachthree-dimensional point (S3049). Next, the three-dimensional dataencoding device ends the loop for each LoD (S3050).

The following describes configurations of the three-dimensional dataencoding device and three-dimensional data decoding device according tothe present embodiment. FIG. 82 is a block diagram illustrating aconfiguration of three-dimensional data encoding device 3000 accordingto the present embodiment. Three-dimensional data encoding device 3000includes geometry information encoder 3001, attribute informationre-assigner 3002, and attribute information encoder 3003.

Attribute information encoder 3003 encodes geometry information(geometry) of a plurality of three-dimensional points included in aninput point cloud. Attribute information re-assigner 3002 re-assigns thevalues of attribute information of the plurality of three-dimensionalpoints included in the input point cloud, using the encoding anddecoding results of the geometry information. Attribute informationencoder 3003 encodes the re-assigned attribute information (attribute).Furthermore, three-dimensional data encoding device 3000 generates abitstream including the encoded geometry information and the encodedattribute information.

FIG. 83 is a block diagram illustrating a configuration ofthree-dimensional data decoding device 3010 according to the presentembodiment. Three-dimensional data decoding device 3010 includesgeometry information decoder 3011 and attribute information decoder3012.

Geometry information decoder 3011 decodes the geometry information(geometry) of a plurality of three-dimensional points from a bitstream.Attribute information decoder 3012 decodes the attribute information(attribute) of the plurality of three-dimensional points from thebitstream. Furthermore, three-dimensional data decoding device 3010integrates the decoded geometry information and the decoded attributeinformation to generate an output point cloud.

As described above, the three-dimensional data encoding device accordingto the present embodiment performs the process illustrated in FIG. 84.The three-dimensional data encoding device encodes a three-dimensionalpoint having attribute information. First, the three-dimensional dataencoding device calculates a predicted value of the attributeinformation of the three-dimensional point (S3061). Next, thethree-dimensional data encoding device calculates a prediction residualwhich is the difference between the attribute information of thethree-dimensional point and the predicted value (S3062). Next, thethree-dimensional data encoding device binarizes the prediction residualto generate binary data (S3063). Next, the three-dimensional dataencoding device arithmetic encodes the binary data (S3064).

In this way, the three-dimensional data encoding device is capable ofreducing the code amount of the to-be-coded data of the attributeinformation by calculating the prediction residual of the attributeinformation, and binarizing and arithmetic encoding the predictionresidual.

For example, in arithmetic encoding (S3064), the three-dimensional dataencoding device uses coding tables different for each of bits of binarydata. By doing so, the three-dimensional data encoding device canincrease the coding efficiency.

For example, in arithmetic encoding (S3064), the number of coding tablesto be used is larger for a lower-order bit of the binary data.

For example, in arithmetic encoding (S3064), the three-dimensional dataencoding device selects coding tables to be used to arithmetic encode acurrent bit included in binary data, according to the value of ahigher-order bit with respect to the current bit. By doing so, since thethree-dimensional data encoding device can select coding tables to beused according to the value of the higher-order bit, thethree-dimensional data encoding device can increase the codingefficiency.

For example, in binarization (S3063), the three-dimensional dataencoding device: binarizes a prediction residual using a fixed bit countto generate binary data when the prediction residual is smaller than athreshold value (R_TH); and generates binary data including a first code(n-bit code) and a second code (remaining code) when the predictionresidual is larger than or equal to the threshold value (R_TH). Thefirst code is of a fixed bit count indicating the threshold value(R_TH), and the second code (remaining code) is obtained by binarizing,using exponential-Golomb coding, the value obtained by subtracting thethreshold value (R_TH) from the prediction residual. In arithmeticencoding (S3064), the three-dimensional data encoding device usesarithmetic encoding methods different between the first code and thesecond code.

With this, for example, since it is possible to arithmetic encode thefirst code and the second code using arithmetic encoding methodsrespectively suitable for the first code and the second code, it ispossible to increase coding efficiency.

For example, the three-dimensional data encoding device quantizes theprediction residual, and, in binarization (S3063), binarizes thequantized prediction residual. The threshold value (R_TH) is changedaccording to a quantization scale in quantization. With this, since thethree-dimensional data encoding device can use the threshold valuesuitably according to the quantization scale, it is possible to increasethe coding efficiency.

For example, the second code includes a prefix and a suffix. Inarithmetic encoding (S3064), the three-dimensional data encoding deviceuses different coding tables between the prefix and the suffix. In thisway, the three-dimensional data encoding device can increase the codingefficiency.

For example, the three-dimensional data encoding device includes aprocessor and memory, and the processor performs the above process usingthe memory.

The three-dimensional data decoding device according to the presentembodiment performs the process illustrated in FIG. 85. Thethree-dimensional data decoding device decodes a three-dimensional pointhaving attribute information. First, the three-dimensional data decodingdevice calculates a predicted value of the attribute information of athree-dimensional point (S3071). Next, the three-dimensional datadecoding device arithmetic decodes encoded data included in a bitstreamto generate binary data (S3072). Next, the three-dimensional datadecoding device debinarizes the binary data to generate a predictionresidual (S3073). Next, the three-dimensional data decoding devicecalculates a decoded value of the attribute information of thethree-dimensional point by adding the predicted value and the predictionresidual (S3074).

In this way, the three-dimensional data decoding device is capable ofappropriately decoding the bitstream of the attribute informationgenerated by calculating the prediction residual of the attributeinformation and binarizing and arithmetic decoding the predictionresidual.

For example, in arithmetic decoding (S3072), the three-dimensional datadecoding device uses coding tables different for each of bits of binarydata. With this, the three-dimensional data decoding device is capableof appropriately decoding the bitstream encoded at an increased codingefficiency.

For example, in arithmetic decoding (S3072), the number of coding tablesto be used is larger for a lower bit of the binary data.

For example, in arithmetic decoding (S3072), the three-dimensional datadecoding device selects coding tables to be used to arithmetic decode acurrent bit included in binary data, according to the value of ahigher-order bit with respect to the current bit. With this, thethree-dimensional data decoding device is capable of appropriatelydecoding the bitstream encoded at an increased coding efficiency.

For example, in debinarizaion (S3073), the three-dimensional datadecoding device debinarizes the first code (n-bit code) of a fixed bitcount included in the binary data to generate a first value. Thethree-dimensional data decoding device: determines the first value to bethe prediction residual when the first value is smaller than thethreshold value (R_TH); and, when the first value is larger than orequal to the threshold value (R_YH), generates a second value bydebinarizing the second code (remaining code) which is anexponential-Golomb code included in the binary data and adds the firstvalue and the second value, thereby generating a prediction residual. Inthe arithmetic decoding (S3072), the three-dimensional data decodingdevice uses arithmetic decoding methods different between the first codeand the second code.

With this, the three-dimensional data decoding device is capable ofappropriately decoding the bitstream encoded at an increased codingefficiency.

For example, the three dimensional data decoding device inversequantizes the prediction residual, and, in addition (S3074), adds thepredicted value and the inverse quantized prediction residual. Thethreshold value (R_TH) is changed according to a quantization scale ininverse quantization.

With this, the three-dimensional data decoding device is capable ofappropriately decoding the bitstream encoded at an increased codingefficiency.

For example, the second code includes a prefix and a suffix. Inarithmetic decoding (S3072), the three-dimensional data decoding deviceuses different coding tables between the prefix and the suffix. Withthis, the three-dimensional data decoding device is capable ofappropriately decoding the bitstream encoded at an increased codingefficiency.

For example, the three-dimensional data decoding device includes aprocessor and memory, and the processor performs the above-describedprocess using the memory.

Embodiment 10

When the three-dimensional data encoding device arithmetically encodesbinarized data of the prediction residual for attribute information item(attribute information) for the three-dimensional point to be encodedaccording to the method of encoding the attribute information item usingprediction, the encoding table may be changed depending on the value ofthe level of detail (LoD) in LoD scheme to which the three-dimensionalpoint to be encoded belongs (that is, depending on at which LoD thethree-dimensional point lies).

In the arithmetic encoding based on the LoD scheme, for example, thearithmetic encoding sequentially occurs from the top LoD to the bottomLoD. Attribute information items (pieces of attribute information) on aplurality of three-dimensional points that lie at the same layer arearithmetically encoded using the same encoding table. The arithmeticencoding may sequentially occur from the bottom LoD to the top LoD. Inthe present embodiment, the encoding table used for at least one of aplurality of LoDs is a table that is not dependent on the encodingtables used for the other layers.

For example, in an upper LoD, the three-dimensional points belonging tothe layer are at longer distances from each other, so that theprediction is difficult, and as a result, the prediction residual can begreater. On the other hand, in a lower LoD, the three-dimensional pointsbelonging to the layer are at shorter distances from each other, so thatthe precision of the prediction is high, and as a result, the predictionresidual can be smaller. In short, the probability of the occurrencepattern of the prediction residual can be significantly differentbetween an upper LoD and a lower LoD. For this reason, thethree-dimensional data encoding device can improve the coding efficiencyby using different encoding tables for different LoDs whenarithmetically encoding the prediction residuals.

Specifically, as a method of arithmetically encoding an n-bit code in aprediction residual for a target three-dimensional point to be encoded,the three-dimensional data encoding device arithmetically encodes then-bit code by using a different encoding table (probability table) foreach bit and using a different encoding table depending on the value ofthe LoD to which the three-dimensional point to be encoded belongs. Inthis process, the three-dimensional data encoding device may change thenumber of encoding tables used for each bit.

For example, the three-dimensional data encoding device may perform thearithmetic encoding of leading bit b0 of the n-bit code by switchingamong 1 x NumLoD encoding tables (note that NumLoD denotes the totalnumber of LoDs) depending on the value of the LoD to which the targetthree-dimensional point to be encoded belongs, and perform thearithmetic encoding of next bit b1 by switching among 2 x NumLoDencoding tables depending on the value (0 or 1) of b0 and the value ofthe LoD to which the target three-dimensional point to be encodedbelongs. Similarly, the three-dimensional data encoding device mayarithmetically encode next bit b2 by switching among four encodingtables depending on the value (0 to 3) of b0b1 and the value of the LoDto which the target three-dimensional point to be encoded belongs.

As described above, when the three-dimensional data encoding devicearithmetically encodes each bit bn−1 of an n-bit code, thethree-dimensional data encoding device may use 2^(n−1) X NumLoD encodingtables and perform the encoding by switching among the 2^(n−1) X NumLoDencoding tables depending on the value (occurrence pattern) of the bitspreceding bit bn−1 and the value of the LoD to which the targetthree-dimensional point to be encoded belongs.

In this way, the three-dimensional data encoding device can encode eachbit by using an appropriate encoding table and therefore can improve thecoding efficiency.

Note that the number of the encoding tables usable for each bit may bereduced. That is, all the encoding tables that can be used for each bitdo not have to be independent from each other (or, in order words,different from each other), and some of the encoding tables that can beused for each bit may overlap with each other (for example, some of theencoding tables may be the same, and/or some of the encoding tables maybe dependent on each other).

For example, three-dimensional data encoding device may arithmeticallyencode each bit bn−1 by switching among 2^(m)× NumLoD encoding tablesdepending on the value (occurrence pattern) of m bits preceding bit bn−1(where m<n−1).

In this way, the three-dimensional data encoding device can improve thecoding efficiency while reducing the number of the encoding tables usedfor each bit.

Note that the three-dimensional data encoding device may update theoccurrence probability of 0 and 1 in each encoding table based on thevalue of binarized data that has actually occurred.

The three-dimensional data encoding device may also reduce theprocessing amount by fixing the occurrence probability of 0 and 1 inencoding tables for some bits and thereby reducing the number of updatesof the occurrence probability.

For example, in a case where the n-bit code is b0b1b2 . . . bn−1, thenumber of the encoding tables for b0 is 1× NumLoD (CTb0[01, . . . ,CTb0[NumLoD−11). The number of the encoding tables for b1 is 2× NumLoD(CTb10[0], . . . , CTb10[NumLoD−11, CTb11[0], . . . , CTb11[NumLoD−11).The three-dimensional data encoding device changes the encoding table tobe used depending on the value of b0 (0 to 1) and the value of LoD.

The number of the encoding tables for b2 is 4× NumLoD (CTb20[01, . . . ,CTb20 [NumLoD−1], CTb21 [0], . . . , CTb21 [NumLoD−1], CTb22 [0], . . ., CTb22 [NumLoD−1], CTb23 [0], . . . , CTb23[NumLoD−1]). Thethree-dimensional data encoding device changes the encoding table to beused depending on the value of b0b1 (0 to 3) and the value of LoD.

The number of the encoding tables for bn−1 is 2^(n−1)×NumLoD (CTbn0 [0],. . . , CTb n0 [NumLoD−1], . . . , CTbn(2^(n−1)1) [0], . . . ,CTbn(2^(n−1)-1)[NumLoD−1]). The three-dimensional data encoding devicechanges the encoding table depending on the value of b0b1 . . . bn−2 (0to 2^(n−1)-1) and the value of LoD.

Note that the three-dimensional data encoding device may apply an m-aryarithmetic coding (m=2n) that sets a value from 0 to 2^(n−1) for then-bit code without binarizing the n-bit code. In that case, thethree-dimensional data encoding device may use NumLoD encoding tablesfor the m-ary arithmetic encoding, and switch among the encoding tablesfor the m-ary arithmetic encoding depending on the value of the LoD towhich the target three-dimensional point to be encoded belongs.

In this way, the three-dimensional data encoding device can select anappropriate encoding table for each LoD and improve the codingefficiency.

When the three-dimensional data encoding device (on the encoder side)performs the m-ary arithmetic encoding of the n-bit code, thethree-dimensional data decoding device (on the decoder side) can decodethe n-bit code by using the m-ary arithmetic decoding. In that case, thethree-dimensional data decoding device can use NumLoD decoding tablesfor the m-ary arithmetic decoding, and switch among the decoding tablesfor the m-ary arithmetic decoding depending on the value of the LoD towhich the target three-dimensional point to be decoded belongs.

Furthermore, as a method of arithmetically encoding a remaining code ina prediction residual for a target three-dimensional point to beencoded, the three-dimensional data encoding device may arithmeticallyencode the remaining code by using different encoding tables for aprefix part and a suffix part and using a different encoding tabledepending on the value of the LoD to which the target three-dimensionalpoint to be encoded belongs.

For example, the three-dimensional data encoding device may perform thearithmetic encoding of the prefix part of the remaining code byswitching among 1× NumLoD encoding tables (note that NumLoD denotes thetotal number of LoDs) depending on the value of the LoD to which thetarget three-dimensional point to be encoded belongs, and perform thearithmetic encoding of the suffix part of the remaining code byswitching among the 1× NumLoD encoding tables depending on the value ofthe LoD to which the target three-dimensional point to be encodedbelongs. That is, the three-dimensional data encoding device mayarithmetically encode each bit of the prefix part using an encodingtable for prefix for the LoD to which the three-dimensional point to beencoded belongs, and arithmetically encode each bit of the suffix partusing an encoding table for suffix for the LoD to which thethree-dimensional point to be encoded belongs.

As described above, when the three-dimensional data encoding devicearithmetically encodes the prefix part and the suffix part of theremaining code, the three-dimensional data encoding device may encodeeach part by using 1× NumLoD encoding tables and switching among the 1×NumLoD encoding tables depending on the value of the LoD to which thetarget three-dimensional point to be encoded belongs.

In this way, the three-dimensional data encoding device can use anappropriate encoding table for each of the prefix part and the suffixpart and can improve the coding efficiency.

Note that the three-dimensional data encoding device may update theoccurrence probability of 0 and 1 in each encoding table based on thevalue of binarized data that has actually occurred.

The three-dimensional data encoding device may also reduce theprocessing amount by fixing the occurrence probability of 0 and 1 inencoding tables for the prefix part and the suffix part and reducing thenumber of updates of the occurrence probability.

FIG. 86 is a diagram for describing a process in a case where theremaining code according to the present embodiment is an exponentialGolomb code.

The remaining code, which is a part binarized by exponential Golombcoding by the three-dimensional data encoding device, includes theprefix part and the suffix part as shown in FIG. 86. For example, thethree-dimensional data encoding device arithmetically encodes the prefixpart and the suffix part using different encoding tables depending onthe value of the LoD to which the target three-dimensional point to beencoded belongs.

For example, the three-dimensional data encoding device arithmeticallyencodes each bit of the prefix part using an encoding table for prefixfor the LoD to which the target three-dimensional point to be encodedbelongs.

For example, the three-dimensional data encoding device arithmeticallyencodes each bit of the suffix part using an encoding table for suffixfor the LoD to which the target three-dimensional point to be encodedbelongs.

Note that the three-dimensional data encoding device may update theoccurrence probability of 0 and 1 in each encoding table based on thevalue of binarized data that has actually occurred.

The three-dimensional data encoding device may fix the occurrenceprobability of 0 and 1 in either encoding table.

In this way, the three-dimensional data encoding device can reduce thenumber of updates of the occurrence probability and therefore can reducethe processing amount.

For example, the three-dimensional data encoding device may update theoccurrence probability for the prefix part but fix the occurrenceprobability for the suffix part.

When the three-dimensional data encoding device arithmetically encodesthe prediction residual of an attribute information item by switchingamong encoding tables depending on the value of the LoD to which thetarget three-dimensional point to be encoded belongs, thethree-dimensional data encoding device may change the encoding table foreach LoD based on a maximum layer (MaxLoDCT) for which the encodingtable is to be changed. For example, the three-dimensional data encodingdevice may change the encoding table for an LoD that satisfies acondition that LoD<MaxLoDCT. In that case, the three-dimensional dataencoding device may not switch among the encoding tables and use thesame encoding table for LoDs that are higher than MaxLoDCT.

In this way, even if there are a large number of LoDs, thethree-dimensional data encoding device can reduce the number of encodingtables by appropriately setting the value of MaxLoDCT.

Furthermore, the three-dimensional data encoding device may change theencoding table for each LoD based on a minimum layer (MinLoDCT) forwhich the encoding table is to be changed, that is, may change theencoding table for an LoD that satisfies a condition that LoD>MinLoDCT.In that case, the three-dimensional data encoding device may not switchamong the encoding tables and use the same encoding table for LoDs thatare equal to or lower than MinLoDCT.

In this way, even if there are a large number of LoDs, thethree-dimensional data encoding device can reduce the number of encodingtables by appropriately setting the value of MinLoDCT.

Note that the three-dimensional data encoding device may add MaxLoDCT orMinLoDCT to the header of the bitstream.

This allows the three-dimensional data decoding device (decoder) thatreceives and decodes the bitstream to correctly decode the bitstream byarithmetically decoding the bitstream based on the value of LoD and thevalue of MaxLoDCT or MinLoDCT as with the three-dimensional dataencoding device (encoder).

Note that the three-dimensional data encoding device may not add thevalue of MaxLoDCT or MinLoDCT to the header or the like of thebitstream. For example, the value of MaxLoDCT or MinLoDCT may be defined(fixed) by profile, level, or the like of a standard or the like. Inthat case, the three-dimensional data decoding device may decode theencoded three-dimensional point included in the bitstream using thedefined value of MaxLoDCT or MinLoDCT.

FIG. 87 is a diagram for describing a first example of a process inwhich the three-dimensional data encoding device according to thepresent embodiment performs the arithmetic encoding by changing theencoding table for each LoD. Note that CT is an abbreviation of CodingTable.

As shown in FIG. 87, the three-dimensional data encoding device mayperform the arithmetic encoding using different encoding tables for alldifferent LoDs.

FIG. 88 is a diagram for describing a second example of the process inwhich the three-dimensional data encoding device according to thepresent embodiment performs the arithmetic encoding by changing theencoding table for each LoD. More specifically, FIG. 88 shows an exampleof a case where MaxLoDCT=NumLoD−2.

As shown in FIG. 88, based on the maximum layer MaxLoDCT for which theencoding table is to be changed, the three-dimensional data encodingdevice may perform the arithmetic encoding by changing the encodingtable for an LoD that satisfies a condition that LoD<MaxLoDCT.

FIG. 89 is a diagram for describing a third example of the process inwhich the three-dimensional data encoding device according to thepresent embodiment performs the arithmetic encoding by changing theencoding table for each LoD. More specifically, FIG. 89 shows an exampleof a case where MinLoDCT=1.

As shown in FIG. 89, based on the minimum layer MinLoDCT for which theencoding table is to be changed, the three-dimensional data encodingdevice may perform the arithmetic encoding by changing the encodingtable for an LoD that satisfies a condition that LoD>MinLoDCT. MinLoDCTcan be arbitrarily determined in advance.

FIG. 90 is a diagram for describing a fourth example of the process inwhich the three-dimensional data encoding device according to thepresent embodiment performs the arithmetic encoding by changing theencoding table for each LoD. More specifically, FIG. 90 shows an exampleof a case where LastLoDCT=NumLoD−3.

Based on a parameter of a lowest layer LastLoDCT for which the sameencoding table is to be used, the three-dimensional data encoding devicemay perform the arithmetic encoding using an encoding table CT[0] for anLoD that satisfies a condition that LoD LastLoDCT and using an encodingtable CT[1] for an LoD that satisfies a condition that LoD>LastLoDCT.

Note that the three-dimensional data encoding device may add LastLoDCTto the header or the like of the bitstream.

FIG. 91 is a diagram for describing a fifth example of the process inwhich the three-dimensional data encoding device according to thepresent embodiment performs the arithmetic encoding by changing theencoding table for each LoD. More specifically, FIG. 91 shows an exampleof a case where three encoding tables are prepared, LastLoDCT[0]=LoD1,and LastLoDCT[1]=NumLoD−3.

The three-dimensional data encoding device may use N encoding tables,and may perform the arithmetic encoding using an encoding table CT[M]for an LoD that satisfies a condition that LoD LastLoDCT[M] (M=0 toN−1), based on the lowest layer LastLoDCT[N−11, which is a parameter forswitching among the encoding tables.

Note that the three-dimensional data encoding device may add LastLoDCT[N−1] to the bitstream of the header or the like.

FIG. 92 is a diagram for describing a sixth example of the process inwhich the three-dimensional data encoding device according to thepresent embodiment performs the arithmetic encoding by changing theencoding table for each LoD.

The three-dimensional data encoding device may use two encoding tables,and may perform the arithmetic encoding by changing the encoding table.For example, the three-dimensional data encoding device may perform thearithmetic encoding by assigning an encoding table CT[0] to an LoD of aneven number and an encoding table CT[1] to an LoD of an odd number. Thatis, the three-dimensional data encoding device may perform thearithmetic encoding using the encoding table CT[0] for an LoD of an evennumber and perform the arithmetic encoding using the encoding tableCT[1] for an LoD of an odd number.

FIG. 93 is a flowchart for describing a process of arithmetic encodingof a prediction residual performed by the three-dimensional dataencoding device according to the present embodiment.

First, the three-dimensional data encoding device is supposed to encodea quantized value of a target three-dimensional point P (S3101).

The three-dimensional data encoding device then transforms theprediction residual from a signed integer value to an unsigned integervalue (S3102).

The three-dimensional data encoding device then determines whether acondition that the prediction residual<R_TH[LoDN] is satisfied or not(S3103).

Here, R_TH[LoDN] represents the value of R_TH set by thethree-dimensional data encoding device based on the value of LoDN towhich the target three-dimensional point P to be encoded belongs. Notethat R_TH may be the same for all the LoDs when R_TH does not need to bedifferent for each LoD.

If the three-dimensional data encoding device determines that thecondition that the prediction residual<R_TH[LoDN] is satisfied (if Yesin S3103), the three-dimensional data encoding device binarizes theprediction residual into an n-bit code (S3104).

The three-dimensional data encoding device then arithmetically encodesthe n-bit code (S3105).

On the other hand, if the three-dimensional data encoding devicedetermines that the condition that the prediction residual<R_TH[LoDN] isnot satisfied (if No in S3103), the three-dimensional data encodingdevice sets the binarized data of R_TH[LoDN] as an n-bit code (S3106).

The three-dimensional data encoding device arithmetically encodes then-bit code (S3107).

The three-dimensional data encoding device binarizes the value of(prediction residual—R_TH[LoDN]) by exponential Golomb coding, and setsthe binarized value as a remaining code (S3108).

The three-dimensional data encoding device then arithmetically encodesthe set remaining code (S3109).

FIG. 94 is a flowchart showing an example of a process in which thethree-dimensional data encoding device according to the presentembodiment arithmetically encodes an n-bit code. More specifically, FIG.94 is a flowchart for describing a procedure of the arithmetic encodingin a case where the n-bit code of the prediction residual of theattribute information item on a three-dimensional point belonging toLoDN is b0b1b2 . . . bn−1.

First, the three-dimensional data encoding device obtains the n-bit code(=b0b1b2 . . . bn−1) (S3111).

The three-dimensional data encoding device then sets i at 0 and cnt at 1for bi of the n-bit code (S3112).

The three-dimensional data encoding device then arithmetically encodesbi using an encoding table CTbi[cnti[LoDN] (S3113).

The three-dimensional data encoding device then sets cnt at cnt<<1(S3114).

The three-dimensional data encoding device then sets cnt at cnt I bi(S3115).

The three-dimensional data encoding device executes++i (S3116).

The three-dimensional data encoding device then determines whether acondition i<n is satisfied or not (S3117).

If the three-dimensional data encoding device determines that thecondition that i<n is satisfied (if Yes in S3117), the three-dimensionaldata encoding device outputs arithmetically-encoded data of the n-bitcode (S3118).

On the other hand, if the three-dimensional data encoding devicedetermines that the condition that i<n is not satisfied (if No inS3117), the three-dimensional data encoding device returns the processto step S3113.

FIG. 95 is a flowchart showing an example of the process in which thethree-dimensional data encoding device according to the presentembodiment arithmetically encodes the remaining code. More specifically,FIG. 95 is a flowchart for describing a procedure of the arithmeticencoding in a case where the remaining code of the prediction residualof the attribute information item on a three-dimensional point belongingto LoDN is b0b1b2. . . .

First, the three-dimensional data encoding device obtains the remainingcode (=b0b1b2 . . . ) (S3121).

The three-dimensional data encoding device then sets i at 0 and cnt at 1for bi of the remaining code (S3122).

The three-dimensional data encoding device then arithmetically encodesbi using an encoding table for prefix for the LoDN (S3123).

The three-dimensional data encoding device then determines whether acondition that bi==1 is satisfied or not (S3124).

If the three-dimensional data encoding device determines that thecondition that bi==1 is not satisfied (if No in S3124), thethree-dimensional data encoding device executes++i and ++cnt (S3125),and returns the process to step S3123.

On the other hand, if the three-dimensional data encoding devicedetermines that the condition that bi==1 is satisfied (if Yes in S3124),the three-dimensional data encoding device determines whether acondition that cnt>0 is satisfied or not (S3126).

If the three-dimensional data encoding device determines that thecondition that cnt>0 is satisfied (if Yes in S3126), thethree-dimensional data encoding device executes++i (S3127).

The three-dimensional data encoding device then arithmetically encodesbi using an encoding table for suffix for the LoDN (S3128).

The three-dimensional data encoding device then executes —cnt (S3129),and returns the process to step S3126.

On the other hand, if the three-dimensional data encoding devicedetermines that the condition that cnt>0 is not satisfied (if No inS3126), the three-dimensional data encoding device outputs thearithmetically-encoded data of the remaining code (S3130).

Note that, in step S3113 shown in FIG. 94 and steps S3123 and S3128shown in FIG. 95, the three-dimensional data encoding device may changethe encoding table depending on the value of LoDN. If there is no needto change the encoding table depending on the value of LoDN, thethree-dimensional data encoding device may use the same encoding tableregardless of the value of LoDN. When MaxLoDCT is set, thethree-dimensional data encoding device may maintain the value of LoDN ifa condition that LoDN<MaxLoDCT is satisfied, and set LoDN at MaxLoDCT ifthe condition that LoDN<MaxLoDCT is not satisfied. When MinLoDCT is set,the three-dimensional data encoding device may maintain the value ofLoDN if a condition that LoDN>MinLoDCT is satisfied, and set LoDN atMinLoDCT if the condition that LoDN>

MinLoDCT is not satisfied. When LastLoDCT[N−11 is set, thethree-dimensional data encoding device may set LoDN at the value of M ifa condition that LoDN<=LastLoDCT[M] (M=0 to N−1) is satisfied.

FIG. 96 is a flowchart for describing a process of arithmetic decodingof a prediction residual performed by the three-dimensional datadecoding device according to the present embodiment.

First, the three-dimensional data decoding device is supposed to decodethe quantized value of the target three-dimensional point P (S3131).

The three-dimensional data decoding device then arithmetically decodesthe n-bit code (S3132).

The three-dimensional data decoding device then determines whether acondition that the value of the n-bit code==R_TH[LoDN] is satisfied ornot (S3133).

Here, R_TH[LoDN] represents the value of R_TH that is set by thethree-dimensional data encoding device (encoder) based on the value ofLoDN to which the target three-dimensional point P to be decodedbelongs, and decoded from the bitstream. Note that the three-dimensionaldata decoding device may use the value of R_TH decoded from thebitstream, or the value of R_TH defined by profile, level, or the likeof a standard or the like.

If the three-dimensional data decoding device determines that thecondition that the value of the n-bit code==R_TH[LoDN] is satisfied (ifYes in S3133), the three-dimensional data decoding device arithmeticallydecodes the remaining code (S3134).

The three-dimensional data decoding device then calculates the value ofthe remaining code using a table for the exponential Golomb code(S3135).

The three-dimensional data decoding device then sets the predictionresidual at (R_TH[LoDN]+ the value of the remaining code) (S3136).

The three-dimensional data decoding device then transforms the decodedprediction residual from an unsigned integer value to a signed integervalue (S3137).

On the other hand, if the three-dimensional data decoding devicedetermines that the condition that the value of the n-bitcode==R_TH[LoDN] is not satisfied (if No in S3133), thethree-dimensional data decoding device sets the prediction residual atthe value of the n-bit code (S3138), and ends the process.

FIG. 97 is a flowchart showing an example of a process in which thethree-dimensional data decoding device according to the presentembodiment arithmetically decodes the arithmetically-encoded data of then-bit code. More specifically, FIG. 96 is a flowchart for describing aprocedure of the arithmetic decoding in a case where the n-bit code ofthe prediction residual of the attribute information item on athree-dimensional point belonging to LoDN is b0b1b2 . . . bn−1.

First, the three-dimensional data decoding device obtains thearithmetically-encoded data of the n-bit code (S3141).

The three-dimensional data decoding device then sets i at 0 and value at1 for bi of the n-bit code (S3142).

The three-dimensional data decoding device then arithmetically decodesbi using a decoding table CTbi[value][LoDN] (S3143).

The three-dimensional data decoding device then sets value at value<<1(S3144).

The three-dimensional data decoding device then sets value at value I bi(S3145).

The three-dimensional data decoding device executes++i (S3146). Thethree-dimensional data decoding device then determines whether acondition i<n is satisfied or not (S3147).

If the three-dimensional data decoding device determines that thecondition that i<n is satisfied (if Yes in S3147), the three-dimensionaldata decoding device outputs the n-bit code=b0b1b2 . . . bn−1 (S3148).

On the other hand, if the three-dimensional data decoding devicedetermines that the condition that i<n is not satisfied (if No inS3147), the three-dimensional data decoding device returns the processto step S3143.

FIG. 98 is a flowchart showing an example of the process in which thethree-dimensional data decoding device according to the presentembodiment arithmetically decodes the remaining code. More specifically,FIG. 98 is a flowchart for describing a procedure of the arithmeticdecoding in a case where the remaining code of the prediction residualof the attribute information item on a three-dimensional point belongingto LoDN is b0b1b2 . . . .

First, the three-dimensional data decoding device obtains thearithmetically-encoded data of the remaining code (S3151).

The three-dimensional data decoding device then sets i at 0 and cnt at 1for bi of the remaining code (S3152).

The three-dimensional data decoding device then arithmetically decodesbi using a decoding table for prefix for the LoDN (S3153).

The three-dimensional data decoding device then determines whether acondition that bi==1 is satisfied or not (S3154).

If the three-dimensional data decoding device determines that thecondition that bi==1 is not satisfied (if No in S3154), thethree-dimensional data decoding device executes++i and ++cnt (S3155),and returns the process to step S3153.

On the other hand, if the three-dimensional data decoding devicedetermines that the condition that bi==1 is satisfied (if Yes in S3154),the three-dimensional data decoding device determines whether acondition that cnt>0 is satisfied or not (S3156).

If the three-dimensional data decoding device determines that thecondition that cnt>0 is satisfied (if Yes in S3156), thethree-dimensional data decoding device executes++i (S3157).

The three-dimensional data decoding device then arithmetically decodesbi using a decoding table for suffix for the LoDN (S3158).

The three-dimensional data decoding device then executes —cnt (S3159),and returns the process to step S3156.

On the other hand, if the three-dimensional data decoding devicedetermines that the condition that cnt>0 is not satisfied (if No inS3156), the three-dimensional data decoding device outputs the remainingcode=b0b1b2 . . . (S3160).

Note that, in step S3143 shown in FIG. 97 and steps S3153 and S3158shown in FIG. 98, the three-dimensional data decoding device may changethe decoding table depending on the value of LoDN. If there is no needto change the decoding table depending on the value of LoDN, thethree-dimensional data decoding device may use the same decoding tableregardless of the value of LoDN. When MaxLoDCT is set, thethree-dimensional data decoding device may maintain the value of LoDN ifa condition that LoDN<MaxLoDCT is satisfied, and set LoDN at MaxLoDCT ifthe condition that LoDN<MaxLoDCT is not satisfied. When MinLoDCT is set,the three-dimensional data decoding device may maintain the value ofLoDN if a condition that LoDN>MinLoDCT is satisfied, and set LoDN atMinLoDCT if the condition that LoDN>MinLoDCT is not satisfied. WhenLastLoDCT[N−11 is set, the three-dimensional data decoding device mayset LoDN at the value of M if a condition that LoDN LastLoDCT[M] (M=0 toN−1) is satisfied.

FIG. 99 is a block diagram showing a configuration of attributeinformation encoder 3100 provided in the three-dimensional data encodingdevice according to the present embodiment. Note that FIG. 99 showsdetails of an attribute information encoder, among a geometryinformation encoder, an attribute information item reassigner, and theattribute information encoder provided in the three-dimensional dataencoding device.

Attribute information encoder 3100 includes LoD generator 3101,periphery searcher 3102, predictor 3103, prediction residual calculator3104, quantizer 3105, arithmetic encoder 3106, inverse quantizer 3107,decoded value generator 3108, and memory 3109.

LoD generator 3101 generates (sets) a LoD using geometry information ona three-dimensional point.

Periphery searcher 3102 searches for a neighboring three-dimensionalpoint neighboring each three-dimensional point using a result of LoDgeneration by LoD generator 3101 and distance information indicatingdistances between three-dimensional points.

Predictor 3103 generates (calculates) a predicted value of an attributeinformation item on a target three-dimensional point to be encoded.

Prediction residual calculator 3104 calculates (generates) a predictionresidual of the predicted value of the attribute information itemgenerated by predictor 3103.

Quantizer 3105 quantizes the prediction residual of the attributeinformation item calculated by prediction residual calculator 3104.

Arithmetic encoder 3106 arithmetically encodes the prediction residualquantized by quantizer 3105. Arithmetic encoder 3106 outputs a bitstreamincluding the arithmetically encoded prediction residual to thethree-dimensional data decoding device, for example.

Note that the prediction residual may be binarized by quantizer 3105before being arithmetically encoded by arithmetic encoder 3106.

Inverse quantizer 3107 inverse-quantizes the prediction residualquantized by quantizer 3105.

Decoded value generator 3108 generates a decoded value by adding thepredicted value of the attribute information item generated by predictor3103 and the prediction residual inverse-quantized by inverse quantizer3107 together.

Memory 3109 is a memory that stores a decoded value of the attributeinformation item on each three-dimensional point decoded by decodedvalue generator 3108. For example, when generating a predicted value ofa three-dimensional point yet to be encoded, predictor 3103 generatesthe predicted value using a decoded value of the attribute informationitem on each three-dimensional point stored in memory 3109.

FIG. 100 is a block diagram showing a configuration of attributeinformation decoder 3110 provided in the three-dimensional data decodingdevice according to the present embodiment. Note that FIG. 100 showsdetails of an attribute information decoder, among a geometryinformation decoder and the attribute information decoder provided inthe three-dimensional data decoding device.

Attribute information decoder 3110 includes LoD generator 3111,periphery searcher 3112, predictor 3113, arithmetic decoder 3114,inverse quantizer 3115, decoded value generator 3116, and memory 3117.

LoD generator 3111 generates a LoD using geometry information on athree-dimensional point decoded by the geometry information decoder (notshown in FIG. 100).

Periphery searcher 3112 searches for a neighboring three-dimensionalpoint neighboring each three-dimensional point using a result of LoDgeneration by LoD generator 3111 and distance information indicatingdistances between three-dimensional points.

Predictor 3113 generates a predicted value of an attribute informationitem on a target three-dimensional point to be decoded.

Arithmetic decoder 3114 arithmetically decodes the prediction residualin the bitstream obtained from attribute information encoder 3100.

Inverse quantizer 3115 inverse-quantizes the prediction residualarithmetically decoded by arithmetic decoder 3114.

Decoded value generator 3116 generates a decoded value by adding thepredicted value generated by predictor 3113 and the prediction residualinverse-quantized by inverse quantizer 3115 together. Decoded valuegenerator 3116 outputs the decoded attribute information data to anotherdevice, for example.

Memory 3117 is a memory that stores a decoded value of the attributeinformation item on each three-dimensional point decoded by decodedvalue generator 3116. For example, when generating a predicted value ofa three-dimensional point yet to be decoded, predictor 3113 may generatethe predicted value using a decoded value of the attribute informationitem on each three-dimensional point stored in memory 3117.

[Variations]

Next, variations of the present embodiment will be described. In thepresent embodiment, the three-dimensional data encoding deviceinitializes an encoding table before encoding.

Hereinafter, a case where an octree is used and a case where an LoD isused will be described.

<Variation 1: Octree Representation>

FIG. 101 is a diagram showing an example of a case where thethree-dimensional data encoding device according to the presentvariation uses an entropy encoding table using an octree representationfor arithmetic encoding. Note that illustration of some branches isomitted in FIG. 101.

The shape of a part depends on the range of investigation thereof, ofcourse. For example, the density (or sparseness) varies with layer.

For example, in the octree shown in FIG. 101, a lower layer (layer 0 orlayer 1, for example) is sparser than a higher layer (layer 5 or layer6, for example).

For this reason, the three-dimensional data encoding device can improvethe efficiency of the entropy encoding by initializing an encoding tablewhen encoding a layer higher than the layer being currently encoded. Forexample, when sequentially encoding layers 0 to 6, after thethree-dimensional data encoding device encodes layer 3 shown in FIG.101, the three-dimensional data encoding device initializes encodingtable A and then encodes layer 4 shown in FIG. 101 using initializedencoding table A. In this way, the efficiency of the entropy encoding isimproved.

As described above, when encoding occupancy codes for layers, thethree-dimensional data encoding device may initialize an encoding tablefor each layer.

For example, in the example shown in FIG. 101, when encoding occupancycodes for layers N (N=0 to 6), the three-dimensional data encodingdevice may initialize an encoding table before starting encoding of eachlayer.

In this way, the three-dimensional data encoding device can apply theentropy encoding depending on the occurrence pattern of the occupancycode for each layer, and therefore can improve the coding efficiency.

As shown in FIG. 101, the three-dimensional data encoding device may notinitialize encoding table A after initialization of encoding table A forlayer 0 until encoding of layer 2 is completed, may initialize encodingtable A before encoding layer 3, and then may not initialize encodingtable A until encoding of layer 6 is completed.

In this case, the three-dimensional data encoding device can apply theentropy encoding depending on the occurrence pattern of the occupancycodes for each group of layers, and therefore can improve the codingefficiency.

The three-dimensional data encoding device may add information of forwhich layer the encoding table is initialized to the header of theoutput bitstream. Alternatively, the layer for which the encoding tableis initialized may be defined in advance by a standard or the like.

For example, the three-dimensional data encoding device may add a flagthat indicates whether to initialize the encoding table for each layerto the header of the output bitstream.

This allows the three-dimensional data decoding device to determine forwhich layer the decoding table needs to be initialized and therefore tocorrectly decode the bitstream.

Structure information includes layer information on a layer to which thecurrent node (that is, the target node to be encoded) belongs.Specifically, the structure information is information that indicates ageometrical arrangement of occupancy states of peripheral blocks of thetarget node, for example.

FIG. 102 is a flowchart of a three-dimensional data encoding processincluding an adaptive entropy encoding process using the structureinformation (geometrical information) according to the presentvariation.

In a decomposition process, an octree is generated from an initialbounding box for a three-dimensional point. The bounding box is divideddepending on the position of the three-dimensional point in the boundingbox. A subspace that is not empty is further divided. An occupancy codefor a subspace is encoded into an occupancy code in a step describedlater.

First, the three-dimensional data encoding device obtains an inputthree-dimensional point (point cloud) (S3161). The three-dimensionaldata encoding device then determines whether decomposition to a unitlength is completed or not (S3162).

If the decomposition to the unit length is not completed (if No inS3162), the three-dimensional data encoding device generates an octreeby performing decomposition on the target node (S3163).

The three-dimensional data encoding device then obtains structureinformation (a layer structure, for example) (S3164).

The three-dimensional data encoding device then initializes an encodingtable (S3165).

The three-dimensional data encoding device then entropy-encodes theoccupancy code for the target node using the initialized encoding table(S3166). The process from step S3163 to S3166 described above isrepeated until the decomposition to the unit length is completed. If thedecomposition to the unit length is completed (if Yes in S3162), thethree-dimensional data encoding device outputs the bitstream includingthe generated information (S3167).

FIG. 103 is a flowchart of a three-dimensional data decoding processincluding an adaptive entropy decoding process using the structureinformation according to the present variation.

A decomposition process in the decoding is similar to the decompositionprocess in the encoding. The decomposition process in the decodingdiffers from the decomposition process in the encoding in two respects.First, in the decoding process, the initial bounding box is decomposedusing an occupancy code encoded. Second, in the decoding process, if theunit length is reached in the decomposition process by thethree-dimensional data decoding device, the position of the bounding boxis stored as the point of the three-dimensional point.

First, the three-dimensional data decoding device obtains an inputbitstream (the bitstream output by the three-dimensional data encodingdevice in step S3167 in FIG. 102, for example) (S3171). Thethree-dimensional data decoding device then determines whetherdecomposition to a unit length is completed or not (S3172).

If the decomposition to the unit length is not completed (if No inS3172), the three-dimensional data decoding device generates an octreeby performing decomposition on the target node (S3173).

The three-dimensional data decoding device then obtains structureinformation (a layer structure, for example) (S3174).

The three-dimensional data decoding device then initializes an encodingtable (S3175).

The three-dimensional data decoding device then entropy-decodes theoccupancy code for the target node using the initialized encoding table(S3176).

The process from step S3173 to S3176 described above is repeated untilthe decomposition to the unit length is completed. If the decompositionto the unit length is completed (if Yes in S3172), the three-dimensionaldata decoding device outputs the bitstream including the generatedinformation (S3177).

Note that the three-dimensional data encoding device may alwaysinitialize an encoding table before starting encoding of a node in layer0.

The three-dimensional data encoding device may always perform theinitialization for a certain layer.

The three-dimensional data encoding device may add information on alayer for which an encoding table is initialized to the header or thelike.

FIG. 104 is a flowchart of the initialization process for an encodingtable using structure information according to the present variation.

First, the three-dimensional data encoding device determines whether theencoding of a leading node in layer N is yet to be started and aninitialization flag of an encoding table for layer N is on or not(S3181).

If the three-dimensional data encoding device determines that theencoding of the leading node in layer N is yet to be started and theinitialization flag of the encoding table for layer N is on (if Yes inS3181), the three-dimensional data encoding device initializes theencoding table (S3182).

On the other hand, if the three-dimensional data encoding device doesnot determine that the encoding of the leading node in layer N is yet tobe started and the initialization flag of the encoding table for layer Nis on (if No in S3181), that is, if the three-dimensional data encodingdevice determines that the encoding of the leading node in layer N isnot yet to be started or that the initialization flag of the encodingtable for layer N is not on, the three-dimensional data encoding devicedoes not initialize the encoding table and ends the initializationprocess.

The three-dimensional data encoding device may use layer information onan octree as the structure information to determine whether toinitialize the encoding table used for the entropy encoding of theoccupancy code or not.

Note that FIG. 104 shows an example in which, before encoding theoccupancy code for the leading node in each layer N, thethree-dimensional data encoding device checks the initializationinformation for the layer added to the header of data or the likeobtained along with the three-dimensional points, initializes theencoding table if the initialization information, such as theinitialization flag, is on, and does not initialize the encoding tableif the initialization flag is off.

Note that, although not shown, the same holds true for theinitialization process by the three-dimensional data decoding device.For example, before encoding the occupancy code for the leading node ineach layer N, the three-dimensional data decoding device checks theinitialization information for the layer added to the header of thebitstream or the like, initializes the decoding table if theinitialization information, such as the initialization flag, is on, anddoes not initialize the decoding table if the initialization flag isoff.

Note that the initialization method for the encoding table is notlimited to the method described above, and the three-dimensional dataencoding device may make the determination of whether to perform theinitialization for a certain layer.

FIG. 105 is a block diagram of three-dimensional data encoding device3120 according to the present variation.

Three-dimensional data encoding device 3120 shown in FIG. 105 includesoctree generator 3121, similarity information calculator 3122, encodingtable initializer 3123, and entropy encoder 3124.

Octree generator 3121 generates an octree from an inputthree-dimensional point, for example, and generates an occupancy codefor each node included in the octree.

Similarity information calculator 3122 obtains geometry information,structure information, or an attribute information item on the currentnode.

Encoding table initializer 3123 initializes an encoding table forentropy-encoding the occupancy code based on layer information on thecurrent node.

Entropy encoder 3124 entropy-encodes the occupancy code using a selectedcontext, thereby generating a bitstream.

Note that entropy encoder 3124 may add information indicating theselected context to the bitstream.

FIG. 106 is a block diagram of three-dimensional data decoding device3130 according to the present variation.

Three-dimensional data decoding device 3130 shown in FIG. 106 includesoctree generator 3131, similarity information calculator 3132, decodingtable initializer 3133, and entropy decoder 3134.

Octree generator 3131 generates an octree from bottom to top, forexample, using information obtained from entropy encoder 3124 shown inFIG. 105.

Similarity information calculator 3132 obtains geometry information,structure information, or an attribute information item on the currentnode.

Decoding table initializer 3133 initializes a decoding table forentropy-decoding the occupancy code based on the layer information onthe current node.

Entropy decoder 3134 entropy-decodes the occupancy code using theselected context, thereby generating a three-dimensional point (pointcloud).

Note that entropy decoder 3134 may obtain the information on theselected context by decoding the information added to the bitstream.

<Variation 2: LoD>

When the three-dimensional data encoding device arithmetically encodesbinarized data of the prediction residual of the attribute informationitem on the target three-dimensional point to be encoded in a method ofencoding the attribute information item using prediction, thethree-dimensional data encoding device may initialize an encoding tabledepending on a change of the value of the LoD to which the targetthree-dimensional point to be encoded belongs (or, in other words, aswitching among LoDs).

For example, in an upper LoD, the three-dimensional points belonging tothe layer are at longer distances from each other, so that theprediction is difficult, and as a result, the prediction residual can begreater. On the other hand, in a lower LoD, the three-dimensional pointsbelonging to the layer are at shorter distances from each other, so thatthe precision of the prediction is high, and as a result, the predictionresidual can be smaller. In short, the probability of the occurrencepattern of the prediction residual can be significantly differentbetween an upper LoD and a lower LoD. For this reason, thethree-dimensional data encoding device can improve the coding efficiencyby initializing the encoding table used for arithmetically encoding theprediction residual when a switching among LoDs occurs.

Specifically, as a method of arithmetically encoding an n-bit code in aprediction residual for a target three-dimensional point to be encoded,the three-dimensional data encoding device arithmetically encodes then-bit code by using a different encoding table (probability table) foreach bit and initializing the encoding table when the value of the LoDto which the three-dimensional point to be encoded belongs is differentfrom the value of the LoD to which the three-dimensional point encodedimmediately before the three-dimensional point belongs. In this process,the three-dimensional data encoding device may change the number ofencoding tables used for each bit.

For example, the three-dimensional data encoding device may perform thearithmetic encoding of leading bit b0 of the n-bit code by using oneencoding table and initializing the encoding table each time the valueof the LoD to which the target three-dimensional point to be encodedbelongs changes.

The three-dimensional data encoding device may arithmetically encodenext bit b1 by using two encoding tables and switching among the twoencoding tables depending on the value (0 or 1) of b0, and initializingthe encoding table each time the value of the LoD to which the targetthree-dimensional point to be encoded belongs changes. Similarly, thethree-dimensional data encoding device may arithmetically encode nextbit b2 by using four encoding tables and switching among the fourencoding tables depending on the value (0 to 3) of b0b1, andinitializing the encoding table each time the value of the LoD to whichthe target three-dimensional point to be encoded belongs changes.

As described above, when the three-dimensional data encoding devicearithmetically encodes each bit bn−1 of an n-bit code, thethree-dimensional data encoding device may perform the encoding by using2^(n−1) encoding tables, switching among the encoding tables dependingon the value (occurrence pattern) of the bits preceding bit bn−1, andinitializing the encoding table each time the value of the LoD to whichthe target three-dimensional point to be encoded belongs changes.

In this way, the three-dimensional data encoding device can perform theencoding by using an appropriate encoding table for each bit and foreach layer and therefore can improve the coding efficiency.

Note that the number of the encoding tables used for each bit may bereduced. That is, all the encoding tables that can be used for each bitdo not have to be independent from each other (or, in order words,different from each other), and some of the encoding tables that can beused for each bit may overlap with each other (for example, some of theencoding tables may be the same, and/or some of the encoding tables maybe dependent on each other).

For example, three-dimensional data encoding device may arithmeticallyencode each bit bn−1 by switching among 2^(m) encoding tables dependingon the value (occurrence pattern) of m bits preceding bit bn−1 (wherem<n−1) and initializing the encoding table each time the value of theLoD to which the target three-dimensional point to be encoded belongschanges.

In this way, the three-dimensional data encoding device can improve thecoding efficiency while reducing the number of the encoding tables usedfor each bit.

Note that the three-dimensional data encoding device may update theoccurrence probability of 0 and 1 in each encoding table based on thevalue of binarized data that has actually occurred.

The three-dimensional data encoding device may also reduce theprocessing amount by fixing the occurrence probability of 0 and 1 inencoding tables for some bits and thereby reducing the number of updatesof the occurrence probability.

For example, in a case where the n-bit code is b0b1b2 . . . bn−1, thenumber of the encoding tables for b0 is 1 (CTb0 (probability table)).

The number of the encoding tables for b1 is 2 (CTb10 and CTb11). Thethree-dimensional data encoding device changes the encoding table to beused depending on the value of b0 (0 to 1).

The number of the encoding tables for b2 is 4 (CTb20, CTb21, CTb22, andCTb23). The three-dimensional data encoding device changes the encodingtable to be used depending on the value of b0b1 (0 to 3).

The number of the encoding tables for bn−1 is 2^(n−1) (CTbn0, CTbn1, . .. , CTbn(2^(n−1)-1)). The three-dimensional data encoding device changesthe encoding table to be used depending on the value of b0b1 . . . bn−2(0 to 2^(n−1)−1).

Note that the three-dimensional data encoding device may initialize theencoding table each time the LoD to be encoded changes.

Note that the three-dimensional data encoding device may apply an m-aryarithmetic coding (m=2n) that sets a value from 0 to 2^(n−1) for then-bit code without binarizing the n-bit code. In this case, thethree-dimensional data encoding device may use one encoding table forthe m-ary arithmetic encoding, and initialize the encoding table for them-ary arithmetic encoding each time the LoD to which the targetthree-dimensional point to be encode belongs changes.

In this way, the three-dimensional data encoding device can select anappropriate encoding table for each LoD and improve the codingefficiency.

When the three-dimensional data encoding device (on the encoder side)performs the m-ary arithmetic encoding of the n-bit code, thethree-dimensional data decoding device (on the decoder side) can decodethe n-bit code by using the m-ary arithmetic decoding. In that case, thethree-dimensional data decoding device can use one decoding table forthe m-ary arithmetic decoding, and initialize the decoding table for them-ary arithmetic decoding each time the LoD to which the targetthree-dimensional point to be decoded belongs changes.

Furthermore, as a method of arithmetically encoding a remaining code ina prediction residual for a target three-dimensional point to beencoded, the three-dimensional data encoding device may arithmeticallyencode the remaining code by using different encoding tables for aprefix part and a suffix part and initializing the encoding table eachtime the value of the LoD to which the target three-dimensional point tobe encoded belongs changes.

For example, the three-dimensional data encoding device mayarithmetically encode the prefix part of the remaining code by using oneencoding table and initializing the encoding table each time the valueof the LoD to which the target three-dimensional point to be encodedbelongs changes.

Furthermore, the three-dimensional data encoding device mayarithmetically encode the suffix part of the remaining code by using oneencoding table and initializing the encoding table each time the valueof the LoD to which the target three-dimensional point to be encodedbelongs changes.

As described above, when the three-dimensional data encoding devicearithmetically encodes the prefix part and the suffix part of theremaining code, the three-dimensional data encoding device may encodeeach part by using one encoding table and initializing the encodingtable each time the value of the LoD to which the targetthree-dimensional point to be encoded belongs changes.

In this way, the three-dimensional data encoding device can use anappropriate encoding table for each of the prefix part and the suffixpart and can improve the coding efficiency.

Note that the three-dimensional data encoding device may update theoccurrence probability of 0 and 1 in each encoding table based on thevalue of binarized data that has actually occurred.

The three-dimensional data encoding device may also reduce theprocessing amount by fixing the occurrence probability of 0 and 1 in theencoding tables for the prefix part and the suffix part and reducing thenumber of updates of the occurrence probability.

FIG. 107 is a diagram for describing a process in a case where theremaining code according to the present variation is an exponentialGolomb code.

The remaining code, which is a part binarized with exponential Golombcoding by the three-dimensional data encoding device, includes theprefix part and the suffix part as shown in FIG. 107. For example, thethree-dimensional data encoding device arithmetically encodes the prefixpart and the suffix part by initializing the encoding table each timethe value of the LoD to which the target three-dimensional point to beencoded belongs changes.

For example, the three-dimensional data encoding device arithmeticallyencodes each bit of the prefix part using the encoding table for prefixby initializing the encoding table for prefix each time the value of theLoD to which the target three-dimensional point to be encoded belongschanges.

Furthermore, for example, the three-dimensional data encoding devicearithmetically encodes each bit of the suffix part using the encodingtable for suffix by initializing the encoding table for suffix each timethe value of the LoD to which the target three-dimensional point to beencoded belongs changes.

Note that the three-dimensional data encoding device may update theoccurrence probability of 0 and 1 in each encoding table based on thevalue of binarized data that has actually occurred.

The three-dimensional data encoding device may fix the occurrenceprobability of 0 and 1 in either encoding table. In this way, thethree-dimensional data encoding device can reduce the number of updatesof the occurrence probability and therefore can reduced the processingamount. For example, the three-dimensional data encoding device mayupdate the occurrence probability for the prefix part but fix theoccurrence probability for the suffix part.

When the three-dimensional data encoding device arithmetically encodesthe prediction residual of an attribute information item by initializingthe encoding table each time the value of the LoD to which the targetthree-dimensional point to be encoded belongs changes, thethree-dimensional data encoding device may initialize the encoding tablefor each LoD based on an end layer (EndLoDCT) for which theinitialization of the encoding table is to be ended, or, specifically,may initialize the encoding table for an LoD that satisfies a conditionthat LoD EndLoDCT. In that case, the three-dimensional data encodingdevice may not initialize the encoding table for an LoD greater thanEndLoDCT.

In this way, even if there are a large number of LoDs, thethree-dimensional data encoding device can reduce the number ofinitializations of the encoding table by appropriately setting the valueof EndLoDCT.

Furthermore, the three-dimensional data encoding device may initializethe encoding table based on a start layer (StartLoDCT) for which theinitialization of the encoding table is to be started, or, specifically,may initialize the encoding table for an LoD that satisfies a conditionthat LoD StartLoDCT. In that case, the three-dimensional data encodingdevice may not initialize the encoding table for an LoD smaller thanStartLoDCT except the initial LoD (LoD0).

In this way, even if there are a large number of LoDs, thethree-dimensional data encoding device can reduce the number ofinitializations of the encoding table by appropriately setting the valueof StartLoDCT.

Note that the three-dimensional data encoding device may add EndLoDCT orStartLoDCT to the header of the bitstream.

This allows the three-dimensional data decoding device (decoder) thatreceives and decodes the bitstream to correctly decode the bitstream byarithmetically decoding the bitstream based on the value of LoD and thevalue of EndLoDCT or StartLoDCT as with the three-dimensional dataencoding device (encoder).

Note that the three-dimensional data encoding device may not add thevalue of EndLoDCT or StartLoDCT to the header or the like of thebitstream. For example, the value of EndLoDCT or StartLoDCT may bedefined (fixed) by profile, layer, or the like of a standard or thelike. In that case, the three-dimensional data decoding device maydecode the encoded three-dimensional point included in the bitstreamusing the defined value of EndLoDCT or StartLoDCT.

FIG. 108 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the presentvariation performs the arithmetic encoding by initializing the encodingtable each time a switching among LoDs occurs. Note that CT is anabbreviation of Coding

Table.

As shown in FIG. 108, the three-dimensional data encoding device mayperform the arithmetic encoding by initializing the encoding table foreach LoD.

FIG. 109 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the presentvariation performs the arithmetic encoding by initializing the encodingtable based on EndLoDCT. Note that FIG. 109 shows an example of a casewhere EndLoDCT=NumLoD−3.

As shown in FIG. 109, based on EndLoDCT that indicates the end layer atwhich the initialization of the encoding table is ended, thethree-dimensional data encoding device may perform the arithmeticencoding by initializing the encoding table for an LoD that satisfies acondition that LoD EndLoDCT. EndLoDCT can be arbitrarily determined inadvance.

FIG. 110 is a diagram for describing an example of the process in whichthe three-dimensional data encoding device according to the presentvariation performs the arithmetic encoding by initializing the encodingtable based on StartLoDCT. Note that FIG. 110 shows an example of a casewhere StartLoDCT=2.

As shown in FIG. 110, based on StartLoDCT that indicates the start layerat which the initialization of the encoding table is started, thethree-dimensional data encoding device may perform the arithmeticencoding by initializing the encoding table for an LoD that satisfies acondition that LoD StartLoDCT. StartLoDCT can be arbitrarily determinedin advance.

FIG. 111 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the presentvariation performs the arithmetic encoding by initializing the encodingtable based on InitLoDCT. More specifically, FIG. 111 shows an exampleof a case where

InitLoDCT=NumLoD−2.

As shown in FIG. 111, based on the parameter InitLoDCT that indicatesthe layer at which the encoding table is to be initialized, thethree-dimensional data encoding device may perform the arithmeticencoding by initializing encoding table CT[0] for an LoD that satisfiesa condition that LoD=InitLoDCT. InitLoDCT can be arbitrarily determinedin advance.

Note that the three-dimensional data encoding device may add InitLoDCTto the header or the like of the bitstream.

FIG. 112 is a diagram for describing an example of a process in whichthe three-dimensional data encoding device according to the presentvariation performs the arithmetic encoding by initializing the encodingtable based on InitLoDCT[N]. More specifically, FIG. 112 shows anexample of a case where InitLoDCT[0]=LoD2, and InitLoDCT[1]=NumLoD—2.The three-dimensional data encoding device initializes the encodingtable for each of the layers LoD2 and NumLoD−2.

As shown in FIG. 112, the three-dimensional data encoding device may useInitLoDCT[N], which is a parameter that prescribes N layers to beinitialized, and initialize the layers indicated by InitLoDCT[N].InitLoDCT can be arbitrarily determined in advance.

Note that the three-dimensional data encoding device may addInitLoDCT[N] to the header or the like of the bitstream.

FIG. 113 is a diagram for describing another example of the process inwhich the three-dimensional data encoding device according to thepresent variation performs the arithmetic encoding by initializing theencoding table based on InitLoDCT[N].

As shown in FIG. 113, the three-dimensional data encoding device mayinitialize the encoding table for a layer that satisfies a conditionthat InitLoDCT[N]=1 and not initialize the encoding table for a layerthat satisfies a condition that InitLoDCT[N]=0.

The three-dimensional data encoding device may add InitLoDCT[N], whichis information that indicates whether to initialize the encoding tablefor each layer, to the bitstream (N denotes the value indicating eachlayer).

The three-dimensional data encoding device may fix the value ofInitLoDCT [0] at 1 and not add the parameter to the bitstream.

FIG. 114 is a diagram showing an example syntax of the bitstreamaccording to the present variation. FIG. 114 is a diagram showing anexample syntax of an attribute header (attribute_header) according tothe present variation. The attribute header is header information of anattribute information item.

As shown in FIG. 114, the attribute header includes number-of-layersinformation (NumLoD), number-of-three-dimensional-points information(NumOfPoint[i]), layer threshold (Thres_Lod[i]),number-of-peripheral-points information (NumNeighorPoint[i], predictionthreshold (THd[i]), quantization scale (QS[i]), and initializationthreshold (InitLoDCT[i]).

The number-of-layers information (NumLoD) indicates the number of LoDsused.

The number-of-three-dimensional-points information (NumOfPoint[i])indicates the number of the three-dimensional points that belong tolayer i.

Note that the three-dimensional data encoding device may addtotal-number-of-three-dimensional-points information (AllNumOfPoint)that indicates the total number of three-dimensional points to anotherheader. In that case, the three-dimensional data encoding device doesnot need to add NumOfPoint[NumLoD−1] to the header. In that case, thethree-dimensional data encoding device can calculateNumOfPoint[NumLoD−1] according to the following formula (Equation B1).

[Math.5] $\begin{matrix}{{{NumOfPoint}\left\lbrack {{NumLoD} - 1} \right\rbrack} = {{AllNumOfPoint} - {\sum\limits_{j = 0}^{{NumLoD} - 2}{{NumOfPoint}\lbrack j\rbrack}}}} & \left( {{Equation}{B1}} \right)\end{matrix}$

In this way, the code amount of the header can be reduced.

The layer threshold (Thres_Lod[i]) is a threshold used for setting layeri. The three-dimensional data encoding device and the three-dimensionaldata decoding device set LoDi in such a manner that the distancesbetween the points in the LoDi are greater than the thresholdThres_Lod[i]. The three-dimensional data encoding device may not add thevalue of Thres_Lod[NumLoD−1] (the lowest layer) to the header. In thatcase, the three-dimensional data decoding device may estimate the valueof Thres_Lod[NumLoD−1] to be 0.

In this way, the code amount of the header can be reduced.

The number-of-peripheral-points information (NumNeighorPoint[i])indicates an upper limit value of the number of the peripheral pointsused for generation of the predicted value for a three-dimensional pointbelonging to layer i. When the number M of peripheral points is smallerthan NumNeighorPoint[i] (M<NumNeighorPoint[i]), the three-dimensionaldata encoding device may calculate the predicted value using Mperipheral points. When the value of NumNeighorPoint[i] does not have tobe different between LoDs, the three-dimensional data encoding devicemay add one item of number-of-peripheral-points information(NumNeighorPoint) used for all the LoDs to the header.

The prediction threshold (THd[i]) indicates an upper limit value of thedistances between the peripheral three-dimensional points used forprediction of the target three-dimensional point to be encoded ordecoded in layer i. The three-dimensional data encoding device and thethree-dimensional data decoding device do not use for prediction anythree-dimensional point the distance of which from the targetthree-dimensional point is greater than THd [i].

Note that, when the value of THd[i] does not have to be differentbetween LoDs, the three-dimensional data encoding device may add oneprediction threshold (THd) used for all the LoDs to the header.

The quantization scale (QS[i]) indicates a quantization scale used forquantization and inverse quantization for layer i.

The initialization threshold (InitLoDCT[i]) is information thatindicates whether to initialize the encoding table for layer i. Forexample, the three-dimensional data encoding device initializes theencoding table for a layer that satisfies a condition thatInitLoDCT[i]=1, and does not initialize the encoding table for a layerthat satisfies a condition that InitLoDCT[i]=0. Note that thethree-dimensional data encoding device may fix the value of InitLoDCT[i]at 1 and not add the parameter to the bitstream. In this way, the codeamount of the header can be reduced.

The three-dimensional data encoding device may entropy-encode at leastone of NumLoD, Thres_Lod[i], NumNeighborPoint[i], THd[i], QS[i], andInitLoDCT[i] and add the resulting code to the header. For example, thethree-dimensional data encoding device may binarize and arithmeticallyencode each value.

Furthermore, the three-dimensional data encoding device may encode eachvalue with a fixed length in order to reduce the processing amount.

Furthermore, the three-dimensional data encoding device may not add atleast one of NumLoD, Thres_Lod[i], NumNeighborPoint[i], THd[i], QS[i],and InitLoDCT[i] to the header. For example, at least one of thesevalues may be defined by profile, level, or the like of a standard orthe like.

In this way, the bit amount of the header can be reduced.

FIG. 115 is a flowchart of a three-dimensional data encoding process bythe three-dimensional data encoding device according to the presentvariation.

First, the three-dimensional data encoding device encodes geometryinformation (geometry) (S3191). For example, the three-dimensional dataencoding device performs the encoding using an octree representation.

After the encoding of the geometry information, if the position of athree-dimensional point is changed because of quantization or the like,the three-dimensional data encoding device reassigns the attributeinformation item on the original three-dimensional point to thethree-dimensional point changed in position (S3192). For example, thethree-dimensional data encoding device performs the reassignment byinterpolation of values of the attribute information items according tothe amount of change in position. For example, the three-dimensionaldata encoding device detects N three-dimensional points yet to bechanged in position close to the three-dimensional position of thethree-dimensional point changed in position, and takes a weightedaverage of the values of the attribute information items on the Nthree-dimensional points. For example, in taking the weighted average,the three-dimensional data encoding device determines the weight basedon the distance between the three-dimensional position of thethree-dimensional point changed in position and each of the Nthree-dimensional points. The three-dimensional data encoding devicedetermines the value obtained by the weighted averaging as the value ofthe attribute information item on the three-dimensional point changed inposition.

If the three-dimensional positions of two or more three-dimensionalpoints are changed to the same three-dimensional position because ofquantization or the like, the three-dimensional data encoding device mayassign an average value of the attribute information items on the two ormore three-dimensional points yet to be changed in position as thevalues of the attribute information items on the three-dimensionalpoints changed in position.

The three-dimensional data encoding device then encodes the reassignedattribute information item (Attribute) (S3193). For example, when thethree-dimensional data encoding device encodes a plurality of kinds ofattribute information items, the three-dimensional data encoding devicemay sequentially encode the plurality of kinds of attribute informationitems. For example, when the three-dimensional data encoding deviceencodes color and degree of reflection as attribute information items,the three-dimensional data encoding device may generate a bitstreamincluding the result of encoding of color followed by the result ofencoding of degree of reflectance.

Note that the order of a plurality of results of encoding of attributeinformation items included in a bitstream is not limited to this orderbut can be any order.

The three-dimensional data encoding device may add informationindicating a starting point of the encoded data of each attributeinformation item in the bitstream to the header or the like.

In this way, the three-dimensional data decoding device can decode anattribute information item that needs to be decoded, and therefore canomit the decoding process for an attribute information item that doesnot need to be decoded. Therefore, the processing amount of thethree-dimensional data decoding device can be reduced.

The three-dimensional data encoding device may encode a plurality ofkinds of attribute information items in parallel, and integrate theresults of the encoding into one bitstream.

In this way, the three-dimensional data encoding device can encode aplurality of kinds of attribute information items at a high speed.

FIG. 116 is a flowchart of the attribute information item encodingprocess (S3193) shown in FIG. 115.

First, the three-dimensional data encoding device sets an LoD (S3201).That is, the three-dimensional data encoding device assigns eachthree-dimensional point to any of a plurality of LoDs.

The three-dimensional data encoding device then starts a loop on an LoDbasis (S3202). That is, the three-dimensional data encoding devicerepeatedly performs the process from step S3203 to step S3212 for eachLoD.

The three-dimensional data encoding device then initializes the encodingtable (S3203).

The three-dimensional data encoding device then starts a loop for eachthree-dimensional point (S3204). That is, the three-dimensional dataencoding device repeatedly performs the process from step S3205 to stepS3211 for each three-dimensional point at a certain LoD. Note that FIG.116 shows encoding of target three-dimensional point P to be encoded.

The three-dimensional data encoding device then searches for a pluralityof peripheral points, which are three-dimensional points present in theperiphery of target three-dimensional point P, that are used forcalculation of a predicted value of target three-dimensional point P tobe processed (S3205).

The three-dimensional data encoding device then calculates a predictedvalue of target three-dimensional point P (S3206). Specifically, thethree-dimensional data encoding device calculates a weighted average ofvalues of the attribute information items on the plurality of peripheralpoints, and sets the obtained value as the predicted value.

The three-dimensional data encoding device then calculates a predictionresidual, which is the difference between the attribute information itemand the predicted value of target three-dimensional point P (S3207).

The three-dimensional data encoding device then calculates a quantizedvalue by quantizing the prediction residual (S3208).

The three-dimensional data encoding device then arithmetically encodesthe quantized value (S3209).

The three-dimensional data encoding device then calculates aninverse-quantized value by inverse quantizing the quantized value(S3210).

The three-dimensional data encoding device then generates a decodedvalue by adding the predicted value to the inverse-quantized value(S3211).

The three-dimensional data encoding device then ends the loop for eachthree-dimensional point (S3212).

The three-dimensional data encoding device also ends the loop for eachLoD (S3213).

FIG. 117 is a flowchart of a three-dimensional data decoding process bythe three-dimensional data decoding device.

First, the three-dimensional data decoding device decodes geometryinformation (geometry) from the bitstream (S3214). For example, thethree-dimensional data decoding device performs the decoding using anoctree representation.

The three-dimensional data decoding device then decodes the attributeinformation item (Attribute) from the bitstream (S3215). For example,when the three-dimensional data decoding device decodes a plurality ofkinds of attribute information items, the three-dimensional datadecoding device may sequentially decode the plurality of kinds ofattribute information items. For example, when the three-dimensionaldata decoding device decodes color and degree of reflection as attributeinformation items, the three-dimensional data decoding device may decodethe result of encoding of color and the result of encoding of degree ofreflectance in the order thereof in the bitstream. For example, if theresult of encoding of color is followed by the result of encoding ofdegree of reflectance in the bitstream, the three-dimensional datadecoding device first decodes the result of encoding of color and thendecodes the result of encoding of degree of reflectance.

Note that the three-dimensional data decoding device can decode theresults of encoding of attribute information items added to thebitstream in any order.

The three-dimensional data decoding device may obtain the informationindicating the starting point of the encoded data of each attributeinformation item in the bitstream by decoding the header or the like.

In this way, the three-dimensional data decoding device can selectivelydecode an attribute information item that needs to be decoded, andtherefore can omit the decoding process for an attribute informationitem that does not need to be decoded. Therefore, the processing amountof the three-dimensional data decoding device can be reduced.

The three-dimensional data decoding device may decode a plurality ofkinds of attribute information items in parallel, and integrate theresults of the decoding into one three-dimensional point cloud.

In this way, the three-dimensional data decoding device can decode aplurality of kinds of attribute information items at a high speed.

FIG. 118 is a flowchart of the attribute information item decodingprocess (S3215) shown in FIG. 117.

First, the three-dimensional data decoding device sets an LoD (S3221).That is, the three-dimensional data decoding device assigns each of aplurality of three-dimensional points having decoded geometryinformation to any of a plurality of LoDs. For example, the method ofthe assignment is the same as the method of assignment used by thethree-dimensional data encoding device.

The three-dimensional data decoding device then starts a loop on an LoDbasis (S3222). That is, the three-dimensional data decoding devicerepeatedly performs the process from step S3223 to step S3230 for eachLoD.

The three-dimensional data decoding device then initializes the decodingtable (S3223).

The three-dimensional data decoding device then starts a loop for eachthree-dimensional point (S3224). That is, the three-dimensional datadecoding device repeatedly performs the process from step S3225 to stepS3229 for each three-dimensional point. Note that FIG. 118 showsdecoding of target three-dimensional point P.

The three-dimensional data decoding device first searches for aplurality of peripheral points, which are three-dimensional pointspresent in the periphery of target three-dimensional point P, that areused for calculation of a predicted value of target three-dimensionalpoint P to be processed (S3225).

The three-dimensional data decoding device then decodes the predictedvalue of target three-dimensional point P (S3226). Specifically, thethree-dimensional data decoding device calculates a weighted average ofvalues of the attribute information items on the plurality of peripheralpoints, and designates the obtained value as the predicted value. Notethat these processes are the same as those in the three-dimensional dataencoding device.

The three-dimensional data decoding device then arithmetically decodesthe quantized value from the bitstream (S3227).

The three-dimensional data decoding device then calculates aninverse-quantized value by inverse-quantizing the decoded quantizedvalue (S3228).

The three-dimensional data decoding device then generates a decodedvalue by adding the predicted value to the inverse-quantized value(S3229).

The three-dimensional data decoding device then ends the loop for eachthree-dimensional point (S3230).

The three-dimensional data decoding device also ends the loop for eachLoD (S3231).

FIG. 119 is a flowchart of an initialization process for an encodingtable performed by the three-dimensional data encoding device accordingto the present variation. Note that FIG. 119 shows an initializationprocess for an encoding table in the process of encoding for LoDi.

First, the three-dimensional data encoding device determines whetherInitLoDCT [i] is 1 for current layer i or not (S3241).

If the three-dimensional data encoding device determines thatInitLoDCT[i] is 1 for current layer i (if Yes in S3241), thethree-dimensional data encoding device initializes the encoding table(S3242).

On the other hand, if the three-dimensional data encoding devicedetermines that InitLoDCT [i] is not 1 for current layer i (if No inS3241), the three-dimensional data encoding device does not initializethe encoding table and ends the initialization process.

FIG. 120 is a block diagram showing a configuration of attributeinformation encoder 3140 provided in the three-dimensional data encodingdevice according to the present variation. Note that FIG. 120 showsdetails of an attribute information encoder, among a geometryinformation encoder, an attribute information item reassigner, and theattribute information encoder provided in the three-dimensional dataencoding device.

Attribute information encoder 3140 includes LoD generator 3141,periphery searcher 3142, predictor 3143, prediction residual calculator3144, quantizer 3145, arithmetic encoder 3146, inverse quantizer 3147,decoded value generator 3148, and memory 3149.

LoD generator 3141 generates an LoD using geometry information on athree-dimensional point.

Periphery searcher 3142 searches for a neighboring three-dimensionalpoint neighboring each three-dimensional point using a result of LoDgeneration by LoD generator 3141 and distance information indicatingdistances between three-dimensional points.

Predictor 3143 generates a predicted value of an attribute informationitem on a target three-dimensional point to be encoded.

Prediction residual calculator 3144 calculates (generates) a predictionresidual of the predicted value of the attribute information itemgenerated by predictor 3143.

Quantizer 3145 quantizes the prediction residual of the attributeinformation item calculated by prediction residual calculator 3144.

Arithmetic encoder 3146 arithmetically encodes the prediction residualquantized by quantizer 3145. Arithmetic encoder 3146 outputs a bitstreamincluding the arithmetically encoded prediction residual to thethree-dimensional data decoding device, for example.

The prediction residual may be binarized by quantizer 3145 before beingarithmetically encoded by arithmetic encoder 3146.

Arithmetic encoder 3146 may initialize the encoding table used for thearithmetic encoding before performing the arithmetic encoding.Arithmetic encoder 3146 may initialize the encoding table used for thearithmetic encoding for each layer. Arithmetic encoder 3146 may output abitstream including information that indicates the position of the layerat which the encoding table is initialized.

Inverse quantizer 3147 inverse-quantizes the prediction residualquantized by quantizer 3145.

Decoded value generator 3148 generates a decoded value by adding thepredicted value of the attribute information item generated by predictor3143 and the prediction residual inverse-quantized by inverse quantizer3147 together.

Memory 3149 is a memory that stores a decoded value of an attributeinformation item on each three-dimensional point decoded by decodedvalue generator 3148. For example, when generating a predicted value ofa three-dimensional point yet to be encoded, predictor 3143 may generatethe predicted value using a decoded value of an attribute informationitem on each three-dimensional point stored in memory 3149.

FIG. 121 is a block diagram showing a configuration of attributeinformation decoder 3150 provided in the three-dimensional data decodingdevice according to the present variation. Note that FIG. 121 showsdetails of an attribute information decoder, among a geometryinformation decoder and the attribute information decoder provided inthe three-dimensional data decoding device.

Attribute information decoder 3150 includes LoD generator 3151,periphery searcher 3152, predictor 3153, arithmetic decoder 3154,inverse quantizer 3155, decoded value generator 3156, and memory 3157.

LoD generator 3151 generates an LoD using geometry information on athree-dimensional point decoded by the geometry information decoder (notshown in FIG. 121).

Periphery searcher 3152 searches for a neighboring three-dimensionalpoint neighboring each three-dimensional point using a result of LoDgeneration by LoD generator 3151 and distance information indicatingdistances between three-dimensional points.

Predictor 3153 generates a predicted value of attribute information itemon a target three-dimensional point to be decoded.

Arithmetic decoder 3154 arithmetically decodes the prediction residualin the bitstream obtained from attribute information encoder 3100 shownin FIG. 120. Note that arithmetic decoder 3154 may initialize thedecoding table used for the arithmetic decoding. Arithmetic decoder 3154initializes the decoding table used for the arithmetic decoding for thelayer for which the encoding process has been performed by arithmeticencoder 3146 shown in FIG. 120. Arithmetic decoder 3154 may initializethe decoding table used for the arithmetic decoding for each layer.Arithmetic decoder 3154 may initialize the decoding table based on theinformation included in the bitstream that indicates the position of thelayer for which the encoding table has been initialized.

Inverse quantizer 3155 inverse-quantizes the prediction residualarithmetically decoded by arithmetic decoder 3154.

Decoded value generator 3156 generates a decoded value by adding thepredicted value generated by predictor 3153 and the prediction residualinverse-quantized by inverse quantizer 3155 together. Decoded valuegenerator 3156 outputs the decoded attribute information data to anotherdevice.

Memory 3157 is a memory that stores a decoded value of an attributeinformation item on each three-dimensional point decoded by decodedvalue generator 3156. For example, when generating a predicted value ofa three-dimensional point yet to be decoded, predictor 3153 generatesthe predicted value using a decoded value of an attribute informationitem on each three-dimensional point stored in memory 3157.

SUMMARY <Three-Dimensional Data Encoding Device>

As described above, the three-dimensional data encoding device accordingto the present embodiment and variations thereof performs the processshown in FIG. 122. Specifically, the three-dimensional data encodingdevice encodes three-dimensional points having an attribute informationitem.

FIG. 122 is a flowchart showing an encoding process by thethree-dimensional data encoding device according to the presentembodiment and variations thereof.

First, the three-dimensional data encoding device classifies each of aplurality of three-dimensional points into any of a plurality of layersincluding a first layer and a second layer (S3251).

The three-dimensional data encoding device then arithmetically encodesan attribute information item on a three-dimensional point to be encodedamong the plurality of three-dimensional points using a first encodingtable if the three-dimensional point to be encoded lies in the firstlayer, and using a second encoding table that is not dependent on thefirst encoding table if the three-dimensional point to be encoded liesin the second layer (S3252).

In this way, the three-dimensional data encoding device can encode theattribute information item using an encoding table appropriate for eachlayer, and therefore, the code amount of the encoded data of theattribute information item can be reduced. That is, thethree-dimensional data encoding device can improve the codingefficiency.

For example, the first encoding table and the second encoding table aredifferent from each other. That is, the first encoding table and thesecond encoding table are different tables and therefore are independentof each other.

In this way, the three-dimensional data encoding device canarithmetically encode the attribute information items on thethree-dimensional points using an encoding table appropriate for eachlayer. Therefore, the three-dimensional data encoding device can furtherimprove the coding efficiency.

For example, the plurality of three-dimensional points each havegeometry information. In this case, in the classification process(S3251), the three-dimensional data encoding device classifies each ofthe three-dimensional points into any of a plurality of layers based onthe geometry information in such a manner that distances betweenthree-dimensional points belonging to an upper layer are longer thandistances between three-dimensional points belonging to a lower layer.

In this way, the three-dimensional data encoding device can encode theattribute information items on the three-dimensional points using anencoding table appropriate for the distances between thethree-dimensional points in each layer. Therefore, the three-dimensionaldata encoding device can further improve the coding efficiency.

For example, the first layer is higher than the second layer in theplurality of layers. In this case, in the arithmetic encoding process(S3252), the three-dimensional data encoding device performs thearithmetic encoding using the first encoding table if the layer in whichthe three-dimensional point to be encoded lies is higher than a firstthreshold layer, and using the second encoding table if the layer inwhich the three-dimensional point to be encoded lies is equal to orlower than the first threshold layer.

In this way, the three-dimensional data encoding device does not need touse many encoding tables, and can further improve the coding efficiency.

For example, the first layer is higher than the second layer in theplurality of layers. In this case, in the arithmetic encoding process(S3252), the three-dimensional data encoding device initializes thefirst encoding table after arithmetically encoding the attributeinformation items on all the three-dimensional points in the firstlayer, and uses the initialized first encoding table to arithmeticallyencode the attribute information items on the three-dimensional pointsin the layer following the first layer.

In this way, the three-dimensional data encoding device can furtherimprove the coding efficiency.

For example, in the arithmetic encoding process (S3252), thethree-dimensional data encoding device sequentially performs thearithmetic encoding from the top layer to the bottom layer. In thiscase, the three-dimensional data encoding device initializes the firstencoding table and arithmetically encodes the attribute information itemon the three-dimensional point to be encoded using the initialized firstencoding table if the layer in which the three-dimensional point to beencoded lies is higher than a second threshold layer, and arithmeticallyencodes the attribute information item on the three-dimensional point tobe encoded using the second encoding table if the layer in which thethree-dimensional point to be encoded lies is equal to or lower than thesecond threshold layer.

For example, in an upper LoD, the three-dimensional points belonging tothe layer are at longer distances from each other, so that theprediction is difficult, and as a result, the prediction residualcalculated from the attribute information item can be greater. On theother hand, in a lower LoD, the three-dimensional points belonging tothe layer are at shorter distances from each other, so that theprecision of the prediction is high, and as a result, the predictionresidual can be smaller. In short, the probability of the occurrencepattern of the prediction residual can be significantly differentbetween an upper LoD and a lower LoD. For this reason, thethree-dimensional data encoding device can improve the coding efficiencyby initializing the encoding table used for arithmetically encoding theattribute information item (specifically, the prediction residual) whenthe relevant LoD is an upper layer.

For example, the second encoding table is the first encoding tableinitialized. That is, the second encoding table is independent of thefirst encoding table as a result of the first encoding table having beeninitialized. As described above, the encoding tables used for thearithmetic encoding for different layers by the three-dimensional dataencoding device may be encoding tables that are different from eachother or encoding tables that are made independent of each other byinitialization thereof. In this way, the three-dimensional data encodingdevice can improve the coding efficiency with a small number of encodingtables.

For example, the three-dimensional data encoding device includes aprocessor and a memory, and the processor performs the processesdescribed above using the memory. The memory may store a control programfor performing the processes described above. The memory may store theencoding tables. The memory may store thresholds, such as the firstthreshold layer and the second threshold layer.

The first threshold layer and the second threshold layer may be the samelayer or different layers, and can be arbitrarily determined in advance.

The expressions “higher than” and “equal to or lower than”, such as “alayer higher than the first threshold layer” and “a layer equal to orlower than the first threshold layer”, are not used in a strict sense.These expressions only mean that the first threshold layer is a boundaryfor classification, and may mean that “a layer equal to or higher thanthe first threshold layer” and “a layer lower than the first thresholdlayer”.

<Three-Dimensional Data Decoding Device>

The three-dimensional data decoding device according to the presentembodiment and variations thereof performs the process shown in FIG.123. Specifically, the three-dimensional data decoding device decodesthree-dimensional points having an attribute information item.

FIG. 123 is a flowchart of a decoding process by the three-dimensionaldata decoding device according to the present embodiment and variationsthereof.

First, the three-dimensional data decoding device classifies each of aplurality of three-dimensional points into any of a plurality of layersincluding a first layer and a second layer (S3261). For example, thethree-dimensional data decoding device decodes the encoded geometryinformation of each of the plurality of three-dimensional pointsincluded in the bitstream received from the three-dimensional dataencoding device, and classifies each of the plurality ofthree-dimensional points into any of the layers based on the decodedgeometry information. Alternatively, the three-dimensional data decodingdevice may obtain information indicating the layer of each of theplurality of three-dimensional points from a source other than thebitstream, and classify each of the plurality of three-dimensionalpoints into any of the plurality of layers based on the obtainedinformation.

The three-dimensional data decoding device then arithmetically decodesan attribute information item on a three-dimensional point to be decodedamong the plurality of three-dimensional points included in thebitstream using a first decoding table if the three-dimensional point tobe decoded lies in the first layer, and using a second decoding tablethat is not dependent on the first decoding table if thethree-dimensional point to be decoded lies in the second layer (S3262).

In this way, the three-dimensional data decoding device canappropriately decode the bitstream of the attribute information itemencoded using an independent encoding table for each layer.

For example, the first decoding table and the second decoding table aredifferent from each other. That is, the first decoding table and thesecond decoding table are different tables and therefore are independentof each other.

In this way, the three-dimensional data decoding device canappropriately decode the arithmetically encoded data of the attributeinformation items on the three-dimensional points using an appropriateencoding table for each layer.

For example, the plurality of three-dimensional points each havegeometry information. In this case, in the classification process(S3261), the three-dimensional data decoding device classifies each ofthe three-dimensional points into any of a plurality of layers based onthe geometry information in such a manner that distances betweenthree-dimensional points belonging to an upper layer are longer thandistances between three-dimensional points belonging to a lower layer.

In this way, the three-dimensional data decoding device canappropriately decode the attribute information items on thethree-dimensional points encoded using an encoding table appropriate forthe distances between the three-dimensional points in each layer.

For example, the first layer is higher than the second layer in theplurality of layers. In this case, in the arithmetic decoding process(S3262), the three-dimensional data decoding device performs thearithmetic decoding using the first decoding table if the layer in whichthe three-dimensional point to be decoded lies is higher than a firstthreshold layer, and using the second decoding table if the layer inwhich the three-dimensional point to be decoded lies is equal to orlower than the first threshold layer.

In this way, the three-dimensional data decoding device canappropriately decode the encoded attribute information items on thethree-dimensional points based on the first threshold layer.

For example, the first layer is higher than the second layer in theplurality of layers. In this case, in the arithmetic decoding process(S3262), the three-dimensional data decoding device initializes thefirst decoding table after arithmetically decoding the attributeinformation items on all the three-dimensional points in the firstlayer, and uses the initialized first decoding table to arithmeticallydecode the attribute information items on the three-dimensional pointsin the layer following the first layer.

In this way, the three-dimensional data decoding device canappropriately decode the attribute information items on thethree-dimensional points encoded using the initialized encoding table.

For example, in the arithmetic decoding process (S3262), thethree-dimensional data decoding device sequentially performs thearithmetic decoding from the top layer to the bottom layer. Furthermore,for example, in the arithmetic decoding process (S3262), thethree-dimensional data decoding device initializes the first decodingtable and arithmetically decodes the attribute information item on thethree-dimensional point to be decoded using the initialized firstdecoding table if the layer in which the three-dimensional point to bedecoded lies is higher than a second threshold layer, and arithmeticallydecodes the attribute information item on the three-dimensional point tobe decoded using the second decoding table if the layer in which thethree-dimensional point to be decoded lies is equal to or lower than thesecond threshold layer.

In this way, the three-dimensional data decoding device canappropriately decode each of attribute information items on a pluralityof three-dimensional points encoded using an encoding table initializedfor some layer.

For example, the second decoding table is the first decoding tableinitialized. That is, the second decoding table is independent of thefirst decoding table as a result of the first decoding table having beeninitialized.

As described above, the decoding tables used for the arithmetic decodingfor different layers by the three-dimensional data decoding device maybe decoding tables that are different from each other or decoding tablesthat are made independent of each other by initialization thereof. Inthis way, the three-dimensional data decoding device can appropriatelydecode the encoded attribute information items on the three-dimensionalpoints even if the attribute information items on the three-dimensionalpoints in each layer are encoded using an initialized encoding table.

For example, the three-dimensional data decoding device includes aprocessor and a memory, and the processor performs the processesdescribed above using the memory. The memory may store a control programfor performing the processes described above. The memory may store thedecoding tables. The memory may store thresholds, such as the firstthreshold layer and the second threshold layer.

The first threshold layer and the second threshold layer may be the samelayer or different layers, and can be arbitrarily determined in advance.A three-dimensional data encoding device, a three-dimensional datadecoding device, and the like according to the embodiments of thepresent disclosure have been described above, but the present disclosureis not limited to these embodiments.

Note that each of the processors included in the three-dimensional dataencoding device, the three-dimensional data decoding device, and thelike according to the above embodiments is typically implemented as alarge-scale integrated (LSI) circuit, which is an integrated circuit(IC). These may take the form of individual chips, or may be partiallyor entirely packaged into a single chip.

Such IC is not limited to an LSI, and thus may be implemented as adedicated circuit or a general-purpose processor. Alternatively, a fieldprogrammable gate array (FPGA) that allows for programming after themanufacture of an LSI, or a reconfigurable processor that allows forreconfiguration of the connection and the setting of circuit cellsinside an LSI may be employed.

Moreover, in the above embodiments, the structural components may beimplemented as dedicated hardware or may be implemented by executing asoftware program suited to such structural components. Alternatively,the structural components may be implemented by a program executor suchas a CPU or a processor reading out and executing the software programrecorded in a recording medium such as a hard disk or a semiconductormemory.

The present disclosure may also be implemented as a three-dimensionaldata encoding method, a three-dimensional data decoding method, or thelike executed by the three-dimensional data encoding device, thethree-dimensional data decoding device, and the like.

Also, the divisions of the functional blocks shown in the block diagramsare mere examples, and thus a plurality of functional blocks may beimplemented as a single functional block, or a single functional blockmay be divided into a plurality of functional blocks, or one or morefunctions may be moved to another functional block. Also, the functionsof a plurality of functional blocks having similar functions may beprocessed by single hardware or software in parallelized or time-dividedmanner.

Also, the processing order of executing the steps shown in theflowcharts is a mere illustration for specifically describing thepresent disclosure, and thus may be an order other than the above order.Also, one or more of the steps may be executed simultaneously (inparallel) with another step.

A three-dimensional data encoding device, a three-dimensional datadecoding device, and the like according to one or more aspects have beendescribed above based on the embodiments, but the present disclosure isnot limited to these embodiments. The one or more aspects may thusinclude forms achieved by making various modifications to the aboveembodiments that can be conceived by those skilled in the art, as wellforms achieved by combining structural components in differentembodiments, without materially departing from the spirit of the presentdisclosure.

INDUSTRIAL APPLICABILITY

The present disclosure is applicable to a three-dimensional dataencoding device and a three-dimensional data decoding device.

1-16. (canceled)
 17. A three-dimensional data encoding method ofencoding a plurality of three-dimensional points each having geometryinformation, the three-dimensional data encoding method comprising:classifying each of the plurality of three-dimensional points into anyof a plurality of layers including a first layer a second layer; andarithmetic-encoding geometry information of a current three-dimensionalpoint among the plurality of three-dimensional points, the arithmeticencoding being performed with reference to (i) a first encoding tablewhen the current three-dimensional point is at the first layer and (ii)a second encoding table not dependent on the first encoding table whenthe current three-dimensional point is at the second layer, wherein thearithmetic-encoding is commonly performed using an octree representationregardless of whether the current three-dimensional point is at thefirst layer or the second layer.
 18. A three-dimensional data decodingmethod of decoding a plurality of encoded three-dimensional points eachhaving geometry information, the three-dimensional data decoding methodcomprising: obtaining each of the plurality of encoded three-dimensionalpoints classified into any of a plurality of layers including a firstlayer and a second layer; and arithmetic-decoding geometry informationof a current three-dimensional point among the plurality of encodedthree-dimensional points included in a bit stream, the arithmeticdecoding being performed with reference to (i) a first decoding tablewhen the current three-dimensional point is at the first layer and (ii)a second decoding table not dependent on the first decoding table whenthe current three-dimensional point is at the second layer, wherein thearithmetic-decoding is commonly performed using an octree representationregardless of whether the current three-dimensional point is at thefirst layer or the second layer.
 19. A three-dimensional data encodingdevice that encodes a plurality of three-dimensional points each havinggeometry information, the three-dimensional data encoding devicecomprising: a processor; and a memory, wherein by using the memory, theprocessor performs: classifying each of the plurality ofthree-dimensional points into any of a plurality of layers including afirst layer a second layer; and arithmetic-encoding geometry informationof a current three-dimensional point among the plurality ofthree-dimensional points, the arithmetic encoding being performed withreference to (i) a first encoding table when the currentthree-dimensional point is at the first layer and (ii) a second encodingtable not dependent on the first encoding table when the currentthree-dimensional point is at the second layer, wherein thearithmetic-encoding is commonly performed using an octree representationregardless of whether the current three-dimensional point is at thefirst layer or the second layer.
 20. A three-dimensional data decodingdevice that decodes a plurality of encoded three-dimensional points eachhaving geometry information, the three-dimensional data decoding devicecomprising: a processor; and a memory, wherein by using the memory, theprocessor performs: obtaining each of the plurality of encodedthree-dimensional points classified into any of a plurality of layersincluding a first layer and a second layer; and arithmetic-decodinggeometry information of a current three-dimensional point among theplurality of encoded three-dimensional points included in a bit stream,the arithmetic decoding being performed with reference to (i) a firstdecoding table when the current three-dimensional point is at the firstlayer and (ii) a second decoding table not dependent on the firstdecoding table when the current three-dimensional point is at the secondlayer, wherein the arithmetic-decoding is commonly performed using anoctree representation regardless of whether the currentthree-dimensional point is at the first layer or the second layer.